Code division multiple access wireless system with closed loop mode using ninety degree phase rotation and beamformer verification

ABSTRACT

A wireless communication system ( 10 ). The system comprises a user station ( 12 ). The user station comprises despreading circuitry ( 22 ) for receiving and despreading a plurality of slots received from at least a first transmit antenna (A 12   1 ) and a second transmit antenna (A 12   2 ) at a transmitting station ( 14 ). Each of the plurality of slots comprises a first channel (DPCH) comprising a first set of pilot symbols and a second channel (PCCPCH) comprising a second set of pilot symbols. The user station further comprises circuitry ( 50 ) for measuring a first channel measurement (α 1,n ) for each given slot in the plurality of slots from the first transmit antenna and in response to the first set of pilot symbols in the given slot. The user station further comprises circuitry ( 50 ) for measuring a second channel measurement (α 2,n ) for each given slot in the plurality of slots from the second transmit antenna and in response to the first set of pilot symbols in the given slot. The user station further comprises circuitry ( 52 ) for measuring a phase difference value (φ 2 (n)) for each given slot in the plurality of slots in response to the first channel measurement and the second channel measurement for the given slot and in response to a ninety degree rotation of the given slot relative to a slot which was received by the despreading circuitry immediately preceding the given slot.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This application claims the benefit, under 35 U.S.C. §120, of divisionalU.S. application Ser. No. 09/635,715, filed Aug. 9, 2000, now U.S. Pat.No. 6,831,943 which claims the benefit under 35 U.S.C. §119(e)(1), ofU.S. Provisional Application No. 60/148,972, filed Aug. 13, 1999, andincorporated herein by this reference.

CROSS-REFERENCES TO RELATED APPLICATIONS

Not Applicable.

BACKGROUND OF THE INVENTION

The present embodiments relate to wireless communications systems and,more particularly, to a closed-loop mode of operation for such systems.

Wireless communications have become very prevalent in business,personal, and other applications, and as a result the technology forsuch communications continues to advance in various areas. One suchadvancement includes the use of spread spectrum communications,including that of code division multiple access (“CDMA”). In suchcommunications, a user station (e.g., a hand held cellular phone)communicates with a base station, where typically the base stationcorresponds to a “cell.” Further, CDMA systems are characterized bysimultaneous transmission of different data signals over a commonchannel by assigning each signal a unique code. This unique code ismatched with a code of a selected user station within the cell todetermine the proper recipient of a data signal. CDMA continues toadvance and with such advancement there has brought forth a nextgeneration wideband CDMA (“WCDMA”). WCDMA includes alternative methodsof data transfer, one being frequency division duplex (“FDD”) andanother being time division duplex (“TDD”).

Due to various factors including the fact that CDMA communications arealong a wireless medium, an originally transmitted communication from abase station to a user station may arrive at the user station atmultiple and different times. Each different arriving signal that isbased on the same original communication is said to have a diversitywith respect to other arriving signals originating from the sametransmitted communication. Further, various diversity types may occur inCDMA communications, and the CDMA art strives to ultimately receive andidentify the originally transmitted data by exploiting the effects oneach signal that are caused by the one or more diversities affecting thesignal.

One type of CDMA diversity occurs because a transmitted signal from abase station is reflected by objects such as the ground, mountains,buildings, and other things that it contacts. As a result, a same singletransmitted communication may arrive at a receiving user station atnumerous different times, and assuming that each such arrival issufficiently separated in time, then each different arriving signal issaid to travel along a different channel and arrive as a different“path.” These multiple signals are referred to in the art as multiplepaths or multipaths. Several multipaths may eventually arrive at theuser station and the channel traveled by each may cause each path tohave a different phase, amplitude, and signal-to-noise ratio (“SNR”).Accordingly, for one communication from one base station to one userstation, each multipath is originally a replica of the same originallytransmitted data, and each path is said to have time diversity relativeto other multipath(s) due to the difference in arrival time which causesdifferent (uncorrelated) fading/noise characteristics for eachmultipath. Although multipaths carry the same user data to the receiver,they may be separately recognized by the receiver based on the timing ofarrival of each multipath. More particularly, CDMA communications aremodulated using a spreading code which consist of a series of binarypulses, and this code runs at a higher rate than the symbol data rateand determines the actual transmission bandwidth. In the currentindustry, each piece or CDMA signal transmitted according to this codeis said to be a “chip,” where each chip corresponds to an element in theCDMA code. Thus, the chip frequency defines the rate of the CDMA code.Given the use of transmission of the CDMA signal using chips, thenmultipaths separated in time by more than one of these chips aredistinguishable at the receiver because of the low auto-correlations ofCDMA codes as known in the art.

In contrast to multipath diversity which is a natural phenomenon, othertypes of diversity are sometimes designed into CDMA systems in an effortto improve SNR, thereby improving other data accuracy measures (e.g.,bit error rate (“BER”), frame error rate (“FER”), and symbol error rate(“SER”)). An example of such a designed diversity scheme is antennadiversity and is introduced here since it pertains to the communicationmethodology used in the preferred embodiments discussed later. Lookingfirst in general to antenna diversity, which is sometimes referred to asantenna array diversity, such diversity describes a wireless systemusing more than one antenna by a same station. Antenna diversity oftenproves useful because fading is independent across different antennas.Further, the notion of a station using multiple antennas is oftenassociated with a base station using multiple antennas to receivesignals transmitted from a single-antenna mobile user station, althoughmore recently systems have been proposed for a base station usingmultiple antennas to transmit signals transmitted to a single-antennamobile station. The present embodiments relate more readily to the caseof a base station using multiple transmit antennas and, thus, thisparticular instance is further explored below.

The approach of using more than one transmit antenna at the base stationis termed transmit antenna diversity. As an example in the field ofmobile communications, a base station transmitter is equipped with twoantennas for transmitting to a single-antenna mobile station. The use ofmultiple antennas at the base station for transmitting has been viewedas favorable over using multiple antennas at the mobile station becausetypically the mobile station is in the form of a hand-held or comparabledevice, and it is desirable for such a device to have lower power andprocessing requirements as compared to those at the base station. Thus,the reduced resources of the mobile station are less supportive ofmultiple antennas, whereas the relatively high-powered base station morereadily lends itself to antenna diversity. In any event, transmitantenna diversity also provides a form of diversity from which SNR maybe improved over single antenna communications by separately processingand combining the diverse signals for greater data accuracy at thereceiver. Also in connection with transmit antenna diversity and tofurther contrast it with multipath diversity described above, note thatthe multiple transmit antennas at a single station are typically withinseveral meters (e.g., three to four meters) of one another, and thisspatial relationship is also sometimes referred to as providing spatialdiversity. Given the spatial diversity distance, the same signaltransmitted by each antenna will arrive at a destination (assuming noother diversity) at respective times that relate to the distance betweenthe transmitting antennas. However, the difference between these timesis considerably smaller than the width of a chip and, thus, the arrivingsignals are not separately distinguishable in the same manner as aremultipaths described above.

Given the development of transmit antenna diversity schemes, two typesof signal communication techniques have evolved to improve datarecognition at the receiver given the transmit antenna diversity,namely, closed loop transmit diversity and open loop transmit diversity.Both closed loop transmit diversity and open loop transmit diversityhave been implemented in various forms, but in all events the differencebetween the two schemes may be stated with respect to feedback.Specifically, a closed loop transmit diversity system includes afeedback communication channel while an open loop transmit diversitysystem does not. More particularly for the case of the closed looptransmit diversity system, a receiver receives a communication from atransmitter and then determines one or more values, or estimates, of thechannel effect imposed on the received communication. The receiver thencommunicates (i.e., feeds back) one or more representations of thechannel effect to the transmitter, so the transmitter may then modifyfuture communication(s) in response to the channel effect. For purposesof the present document, the feedback values are referred to asbeamformer coefficients in that they aid the transmitter in forming itscommunication “beam” to a user station.

With the advancement of CDMA and WCDMA there has been a comparabledevelopment of corresponding standards. For instance, a considerablestandard that has developed, and which continues to evolve, inconnection with WCDMA is the 3^(rd) Generation partnership Project(“3GPP”) for wireless communications, and it is also reflected in 3GPP 2systems. Under 3GPP, closed loop antenna diversity for WCDMA must besupported, and in the past 3GPP set forth a closed loop operationalmethod that alternates between three different communication modes. Thechoice of a mode at a given time is dictated by the Doppler fading rateof a particular user station receiver; in other words, since userstations are likely to be mobile, then due to the mobility as well asother factors there is likely to be an amount of Doppler fading in thesignals received by such a user station from a base station and thisfading affects the choice of a closed loop mode. In addition to thedifferent fading rates gibing rise to the selection of one of the threeprior art modes of operation, each mode differs in certain respects. Onedifference is based on how the beamformer coefficients are quantized bythe user station, and other differences also apply to different ones ofthe modes. Such differences are detailed later. In any event, note hereby way of background that generally there is a tradeoff among the threemodes, where greater resolution in the feedback information, and hence agreater level of beamformer control, is achieved at the expense ofincreased feedback and processing delay.

The preceding three modes have proven to achieve a considerable level ofperformance as measurable in various manners, such as BER, FER, or SNR;however, the present inventors also have identified various drawbackswith the overall three mode approach. For example, a certain level ofcomplexity is required to implement the necessary algorithm to switchbetween the three different modes in response to changes in Dopplerfading. As another example, an alternative approach may be implementedusing one mode which provides results that match or outperform theresults achieved by the prior art modes 1 and 2 across the Dopplerfrequencies for which those prior art modes are used. Still otherbenefits may be ascertainable by one skilled in the art given a furtherunderstanding of the preferred embodiments, as should be accomplishedfrom the detailed description provided below.

BRIEF SUMMARY OF THE INVENTION

In the preferred embodiment, there is a wireless communication system.The system comprises a user station. The user station comprisesdespreading circuitry for receiving and despreading a plurality of slotsreceived from at least a first transmit antenna and a second transmitantenna at a transmitting station. Each of the plurality of slotscomprises a first channel comprising a first set of pilot symbols and asecond channel comprising a second set of pilot symbols. The userstation further comprises circuitry for measuring a first channelmeasurement for each given slot in the plurality of slots from the firsttransmit antenna and in response to the first set of pilot symbols inthe given slot. The user station further comprises circuitry formeasuring a second channel measurement for each given slot in theplurality of slots from the second transmit antenna and in response tothe first set of pilot symbols in the given slot. The user stationfurther comprises circuitry for measuring a phase difference value foreach given slot in the plurality of slots in response to the firstchannel measurement and the second channel measurement for the givenslot and in response to a ninety degree rotation of the given slotrelative to a slot which was received by the despreading circuitryimmediately preceding the given slot.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING

FIG. 1 illustrates a closed loop transmit antenna diversity systemwithin which the preferred embodiments may be implemented.

FIG. 2 illustrates an expanded view of selected blocks of user station14 from FIG. 1.

FIG. 3 illustrates a graph to depict the prior art mode 1 mapping of achannel measurement to one of two different phase shift values.

FIG. 4 illustrates four graphs to depict the prior art mode 2 mapping ofchannel measurements according to respective 45 degree rotations, wherefor each rotation the channel measurement is mapped to one of twodifferent phase shift values.

FIG. 5 illustrates two graphs to depict the mapping of channelmeasurements according to the preferred embodiment broad range closedloop mode according to respective 90 degree rotations, where for eachrotation the channel measurement is mapped to one of two different phaseshift values.

FIG. 6 illustrates a block diagram of the functional operation ofbeamformer coefficient computation block 52 and beamformer coefficientbinary encode block 54 from FIG. 2 and according to the preferredembodiment.

FIG. 7 illustrates a block diagram of channel estimation and beamformerverification block 56 from FIG. 2 and according to the preferredembodiment.

FIG. 8 illustrates a block diagram of a first implementation of abeamformer verification block 100 ₁ that may readily implemented asbeamformer verification block 100 from FIG. 7, and which operatesaccording to a two rotating hypothesis testing method.

FIG. 9 illustrates a block diagram of a second implementation of abeamformer verification block 100 ₂ that also may be implemented asbeamformer verification block 100 from FIG. 7, and which operatesaccording to a four hypothesis single shot testing.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 illustrates a closed loop transmit antenna diversity system 10within which the preferred embodiments may be implemented, and alsowhich in a block form may represent the prior art. Accordingly, thefollowing discussion first examines system 10 in a general fashion asapplying to both the preferred embodiments and the prior art, followedby a detailed discussion with additional illustrations of the particularmodifications to system 10 to implement the preferred embodiments.

Turning to system 10 of FIG. 1, it includes a transmitter 12 and areceiver 14. By way of example, assume that transmitter 12 is a basestation 12 while receiver 14 is a mobile user station 14. Also, for thesake of simplifying the discussion, each of these components isdiscussed separately below. Lastly, note that the dosed loop techniqueimplemented by system 10 is sometimes referred to in the art as atransmit adaptive array (“TxAA”), while other dosed loop techniques alsoshould be ascertainable by one skilled in the art

Base station 12 receives information bits B_(i) at an input to a channelencoder 13. Channel encoder 13 encodes the information bits B_(i) in aneffort to improve raw bit error rate. Various encoding techniques may beused by channel encoder 13 and as applied to bits B_(i), with examplesincluding the use of convolutional code, block code, turbo code,concatenated codes, or a combination of any of these codes. The encodedoutput of channel encoder 13 is coupled to the input of an interleaver15. Interleaver 15 operates with respect to a block of encoded bits andshuffles the ordering of those bits so that the combination of thisoperation with the encoding by channel encoder 13 exploits the timediversity of the information. For example, one shuffling technique thatmay be performed by interleaver 15 is to receive bits in a matrixfashion such that bits are received into a matrix in a row-by-rowfashion, and then those bits are output from the matrix to a symbolmapper 16 in a column-by-column fashion. Symbol mapper 16 then convertsits input bits to symbols, designated generally as S_(i). The convertedsymbols S_(i) may take various forms, such as quadrature phase shiftkeying (“QPSK”) symbols, binary phase shift keying (“BPSK”) symbols, orquadrature amplitude modulation (“QAM”) symbols. In any event, symbolsS_(i) may represent various information such as user data symbols, aswell as pilot symbols and control symbols such as transmit power control(“TPC”) symbols and rate information (“RI”) symbols. Symbols S_(i) arecoupled to a modulator 18. Modulator 18 modulates each data symbol bycombining it with, or multiplying it times, a CDMA spreading sequencewhich can be a pseudo-noise (“PN”) digital signal or PN code or otherspreading codes (i.e., it utilizes spread spectrum technology). In anyevent, the spreading sequence facilitates simultaneous transmission ofinformation over a common channel by assigning each of the transmittedsignals a unique code during transmission. Further, this unique codemakes the simultaneously transmitted signals over the same bandwidthdistinguishable at user station 14 (or other receivers). Modulator 18has two outputs, a first output 18 ₁ connected to a multiplier 20 ₁ anda second output 18 ₂ connected to a multiplier 20 ₂. Generally, each ofmultipliers 20 ₁ and 20 ₂, for a communication slot n, receives acorresponding and per-slot decoded weight value, ω_(1,T)(n) andω_(2,T)(n), from a feedback decode and process block 21. Feedback decodeand process block 21 provides weighted values ω_(1,T)(n) and ω_(2,T)(n)in response to values ω₁(n) and ω₂(n), respectively, as furtherdiscussed below. Each of multiplier 20 ₁ and 20 ₂ multiplies therespective value ω_(1,T)(n) and ω_(2,T)(n) times the correspondingoutput 18 ₁ or 18 ₂ from modulator 18 and, in response, each ofmultipliers 20 ₁ and 20 ₂ provides an output to a respective transmitantenna A12 ₁ and A12 ₂, where antennas A12 ₁ and A12 ₂ areapproximately three to four meters apart from one another. As detailedlater, in applying the various modes of operation in the prior art, theoperation of multiplier 20 ₁ is based on normalized value (i.e.,ω_(1,T)(n) is normalized), while the operation of multiplier 20 ₂ may bebased on a single slot value of ω_(2,T)(n) for certain modes ofoperation while it is based on an average of successively receivedvalues of ω_(2,T)(n) for another mode of operation, and in either caseω_(2,T)(n) is relative to the normalized value of ω_(1,T)(n).

Receiver 14 includes a receive antenna A14 ₁ for receivingcommunications from both of transmit antennas A12 ₁ and A12 ₂. Recallthat such communications may pass by various multipaths, and due to thespatial relationship of transmit antennas A12 ₁ and A12 ₂, eachmultipath may include a communication from both transmit antenna A12 ₁and transmit antenna A12 ₂. In the illustration of FIG. 1, a total of Pmultipaths are shown. Within receiver 14, signals received by antennaA14 ₁ are connected to a despreader 22. Despreader 22 operates in manyrespects according to known principles, such as by multiplying the CDMAsignal times the CDMA code for user station 14 and resolving anymultipaths, thereby producing a despread symbol stream at its output andat the symbol rate. Additional details relating to despreader 22 arealso discussed later in connection with its breakdown of differentchannels of information as received by antenna A14 ₁. The despreadsignals output by despreader 22 are coupled to maximal ratio combining(“MRC”) block 23, and also to a channel evaluator 24. As detailedconsiderably below, channel evaluator 24 performs two different channeldeterminations, and to avoid confusion one such determination isreferred to as channel measurement while the other is referred to aschannel estimation, where both determinations are based at least on theincoming despread data. Further, channel evaluator 24 provides twooutputs. A first output 24 ₁ from channel estimator 24 outputs a channelestimation, designated as ĥ_(n), to MRC block 23. In response toreceiving the channel estimation, MRC block 23 applies the estimation tothe despread data symbols received from despreader 22 using a rakereceiver; however, the application of the estimate to the data may be byway of alternative signal combining methods. A second output 24 ₂ fromchannel evaluator 24 communicates the values ω₁(n) and ω₂(n), introducedearlier, back toward base station 12 via a feedback channel. As alsodetailed below, the values ω₁(n) and ω₂(n) are determined by channelevaluator 24 in response to a channel measurement made by channelevaluator 24. In any event, one skilled in the art should appreciatefrom the preceding that the values ω₁(n) and ω₂(n) are therefore theclosed loop beamformer coefficients introduced above.

Returning to MRC block 23 of user station 14, once it applies thechannel estimation to the despread data, its result is output to adeinterleaver 25 which operates to perform an inverse of the function ofinterleaver 15, and the output of deinterleaver 25 is connected to achannel decoder 26. Channel decoder 26 may include a Viterbi decoder, aturbo decoder, a block decoder (e.g., Reed-Solomon decoding), or stillother appropriate decoding schemes as known in the art. In any event,channel decoder 26 further decodes the data received at its input,typically operating with respect to certain error correcting codes, andit outputs a resulting stream of decoded symbols. Indeed, note that theprobability of error for data input to channel decoder 26 is far greaterthan that after processing and output by channel decoder 26. Forexample, under current standards, the probability of error in the outputof channel decoder 26 may be between 10⁻³ and 10⁻⁶. Finally, the decodedsymbol stream output by channel decoder 26 may be received and processedby additional circuitry in user station 14, although such circuitry isnot shown in FIG. 1 so as to simplify the present illustration anddiscussion.

Having detailed system 10, attention is now returned to itsidentification as a closed loop system. Specifically, system 10 is nameda closed loop system because, in addition to the data communicationchannels from base station 12 to user station 14, system 10 includes thefeedback communication channel for communicating the beamformercoefficients ω₁(n) and ω₂(n) from user station 14 to base station 12;thus, the data communication and feedback communication channels createa circular and, hence, “closed” loop system. Note further thatbeamformer coefficients ω₁(n) and ω₂(n) may reflect various channelaffecting aspects. For example, user station 14 may ascertain a level offading in signals it receives from base station 12, such as may becaused by local interference and other causes such as the Doppler rateof user station 14 (as a mobile station), and in any event where thefading may be characterized by Rayleigh fading. As a result, userstation 14 feeds back beamformer coefficients ω₁(n) and ω₂(n), and thesevalues are processed by feedback decode and process block 21 to producecorresponding values ω_(1,T)(n) and ω_(2,T)(n), which are used bymultipliers 20 ₁ and 20 ₂ to apply those values to various symbols toprovide respective resulting transmitted signals along transmitterantenna A12 ₁ (in response to ω_(1,T)(n)) and along transmitter antennaA12 ₂ (in response to ω_(2,T)(n)). Thus, for a first symbol S₁ to betransmitted by base station 12, it is transmitted as part of a productω_(1,T)(n)S₁ along transmitter antenna A12 ₁ and also as part of aproduct ω_(2,T)(n)S₁ along transmitter antenna A12 ₂. By way ofillustration, therefore, these weighted products are also shown in FIG.1 along their respective antennas.

Having detailed closed loop transmit antenna diversity systems,attention is now directed to the above-introduced 3GPP standard and itschoice of closed loop modes at a given time in response to the Dopplerfading rate of a particular user station receiver. Specifically, thefollowing Table 1 illustrates the three different former 3GPP closeddiversity modes and correlates each mode to an approximate Dopplerfading rate (i.e., frequency).

TABLE 1 Prior Art Mode Doppler fading rate, f(Hz) 1 f > 60 2 10 < f < 603 f < 10In addition to the different fading rates giving rise to the selectionof one the three prior art modes of operation in Table 1, themethodology of each mode differs in certain respects. One difference isbased on how the beamformer coefficients (e.g., ω₁(n) and ω₂(n) fromFIG. 1) are quantized, and other differences also apply to differentones of the modes. Such differences are further explored below.

Looking to the prior art mode 1 of operation from Table 1, it is usedfor relatively high Doppler fading rates, such as would be expected whenthe particular mobile user station 14 with which base station 12 iscommunicating is moving at a relatively large rate of speed. Toaccommodate the higher Doppler fade, mode 1 uses a reduced amount ofquantization for the beamformer coefficients, that is, in mode 1 theuser station feeds back a lesser amount of information to representthese coefficients. More particularly, in mode 1, a beamformercoefficient vector W is fed back by the user station, and for a twoantenna base station let that coefficient vector be represented in thefollowing Equation 1:W=(ω ₁(n),ω₂(n))  Equation 1In Equation 1, the coefficient ω₁(n) is intended to apply to basestation transmit antenna A12 ₁ while the coefficient ω₂(n) is intendedto apply to base station transmit antenna A12 ₂. In practice and tofurther reduce the amount of feedback information, ω₁(n) is normalizedto a fixed value and, thus, it is not necessary to feed it back so longas the normalized value is known by base station 12. Accordingly, whenω₁(n) is normalized, only the value of ω₂(n) may change and is relativeto the fixed value of ω₁(n) and, therefore, ω₂(n) is fed back from userstation 14 to base station 12. Further, in the prior art mode 1, ω₂(n)is only allowed to be one of two values. The quantizations offered bythe vector W therefore may be represented by the following Equations 2and 3:W=(1, 0)  Equation 2W=(1, 1)  Equation 3Thus, mode 1 only requires the feedback of one of two values (i.e., forω₂(n)). Further, note that the conventions in Equations 2 and 3 depictbinary values, while one skilled in the art should appreciate that forthe case of a binary 0, an actual value of −1 is provided on thephysical feedback channel, while for the case of a binary 1, an actualvalue of +1 is provided on the physical feedback channel. Finally, theprior art manner for selecting the value of ω₂(n), that is, betweenbinary 0 and 1, is discussed below.

The prior art mode 1 determination of ω₂(n) is better appreciated fromthe expanded illustration of FIG. 2, where certain blocks of userstation 14 from FIG. 1 are further detailed. Looking to FIG. 2, it againillustrates antenna A14 ₁ providing signals to despreader 22. Despreader22 is expanded in FIG. 2 to illustrate that it includes a despreadingand resolve multipath block 40. Block 40 despreads the incoming signalsfrom two different channels, that is, recall it was earlier introducedthat despreader 22 operates with respect to different channels ofinformation as received by antenna A14 ₁; these different channels arenow illustrated in FIG. 2 as a primary common control physical channel(“PCCPCH”) and a dedicated physical channel (“DPCH”). According to theprior art, the PCCPCH is transmitted by base station 12 as the samechannel to all user stations (i.e., user station 14 and otherscommunicating with base station 12), and it is not weighted in responseto ω₁(n) and ω₂(n). The DPCH, however, is user station specific and itis weighted in response to ω₁(n) and ω₂(n). Both the PCCPCH and DPCHcommunicate in frame formats, where each frame includes a number ofslots; for example, in WCDMA, each frame consists of 16 slots. Furtherwith respect to PCCPCH and DPCH, each slot of those channels commenceswith some pilot symbols and also includes information symbols. Given thepreceding, block 40 operates with respect to each received slot andoutputs both a DPCH symbol stream and PCCPCH symbol stream, and thefurther processing of those streams is discussed below.

The DPCH symbol stream from block 40 is coupled to both an informationsymbol extractor 42 and a pilot symbol extractor 44. Each of blocks 42and 44 operates as suggested by their names, that is, to extract fromthe DPCH symbol stream the DPCH information symbols and the DPCH pilotsymbols, respectively. For sake of reference in this document, the DPCHinformation symbols are represented by x(n) while the DPCH pilot symbolsare represented by y(n), where bold face is used as a convention forthese and other values in this document to indicate that the value is avector. The DPCH information symbols x(n) are output from extractor 42to MRC block 23, while the DPCH pilot symbols y(n) are output fromextractor 44 to channel evaluator 24, as further detailed later.

Returning to despreading and resolve multipath block 40 and its outputof the PCCPCH symbol stream, that stream is coupled to a PCCPCH pilotsymbol extractor 46. PCCPCH pilot symbol extractor 46 extracts thePCCPCH pilot symbols from the PCCPCH symbol stream. For sake ofreference in this document, the PCCPCH pilot symbols are represented byz(n). The PCCPCH pilot symbols z(n) are output from extractor 46 tochannel evaluator 24, as further detailed below.

Looking to channel evaluator 24 in FIG. 2, it includes a channelmeasurement block 50 which receives the PCCPCH pilot symbols z(n) fromextractor 46. Recalling that it was earlier stated that channelevaluator 24 performs both a channel measurement and channel estimationbased at least on the incoming despread data, it is now noted moreparticularly that block 50 performs the channel measurement aspect.Specifically, the PCCPCH pilot symbols are, according to the art,different for each different transmit antenna for a base station; thus,in the present example, the extracted PCCPCH pilot symbols z(n) includesone set of pilot symbols corresponding to base station antenna A12 ₁ andanother set of pilot symbols corresponding to base station antenna A12₂. Since the values of the pilot symbols as transmitted by base station12 are by definition a known value to user station 14, then based on thedifference between the actually received pilot symbols and the knowntransmitted pilot symbols, block 50 determines, for each transmitantenna, a channel measurement reflecting any change in theactually-received pilot symbols. For sake of reference in this document,the channel measurement corresponding to antenna A12 ₁ is indicated asα_(1,n) and the channel measurement corresponding to antenna A12 ₂ isindicated as α_(2,n). Both α_(1,n) and α_(2,n) are output by channelmeasurement block 50 to a beamformer coefficient computation block 52.

Beamformer coefficient computation block 52 computes phase differencevalues, denoted φ₁(n) and φ₂(n), in response to the values α_(1,n) andα_(2,n), where the values φ₁(n) and φ₂(n) as described below are theangular phase differences which are encoded into binary form to createthe respective values of ω₁(n) and ω₂(n) (or just ω₂(n) where ω₁(n) is anormalized value). Recall now that under mode 1 of the prior art, thevalue of ω₂(n) may be only one of two states. Thus, block 52 maps thevalue of α_(2,n) to one of these two states, and this mapping functionis illustrated pictorially in FIG. 3 by a graph 52 g plotted along animaginary and real axis. More particularly, graph 52 g illustrates twoshaded areas 52 ₁ and 52 ₂ corresponding to the two possible values ofω₂(n), and those two values map to two corresponding values of φ₂(n).Specifically, if the channel measurement α_(2,n) ^(H)α_(1,n) fallswithin area 52 ₁, then the value of φ₂(n) is 0 degrees; further, this 0degree value of φ₂(n) is output to a beamformer coefficient binaryencode block 54 which converts the angular value φ₂(n) of 0 degrees intoa corresponding binary value ω₂(n)=0, and the value of ω₂(n)=0 is fedback to base station 12. On the other hand, if the channel measurementα_(2,n) ^(H)α_(1,n) falls within area 52 ₂, then the value of φ₂(n) is πradians; further, this π radian value of φ₂(n) is output to beamformercoefficient binary encode block 54 which converts the angular valueφ₂(n) of π radians into a corresponding binary value ω₂(n)=1, and thevalue of ω₂(n)=1 is fed back to base station 12.

Attention is now directed to an additional aspect of the prior art mode1. Specifically, note that while user station 14 transmits a value ofω₂(n) to base station 12, there quite dearly can be effects imposed onthat transmission as well, that is, there is a channel effect in thefeedback signal from user station 14 to base station 12. Accordingly,from the perspective of base station 12, let {tilde over (ω)}₂(n)represent the signal actually received by base station 12 andcorresponding to the feedback transmission of ω₂(n) from user station14. Next, feedback decode and process block 21 decodes and processes{tilde over (ω)}₂(n) and in response outputs a corresponding value ofω_(2,T)(n) which is multipled by multiplier 18 ₂. As a result, whileideally base station 12 uses the correct value ω₂(n) upon which todetermine ω_(2,T)(n) and to create a resulting product signal (i.e.,ω_(2,T)(n)S_(i))), the feedback channel effect may cause base station 12to use a different value of ω₂(n). For example, user station 14 maytransmit a value of ω₂(n)=0 to base station 12, but due to the feedbackchannel the received value may be {tilde over (ω)}₂(n)=1. Conversely,user station 14 may transmit a value of ω₂(n)=1 to base station 12, butdue to the feedback channel the received value may be {tilde over(ω)}₂(n)=0. In view of these possibilities, user station 14, whenoperating under the prior art mode 1, further implements a processreferred to in the art as beamformer verification or antennaverification, as further detailed below.

Beamformer verification is further introduced by return to the expandedblock diagram in FIG. 2. Specifically, recall it is stated above thatthe DPCH pilot symbols y(n) are output from extractor 44 to channelevaluator 24, and recall also that the DPCH pilot symbols have beenmodified by base station 12 in response to ω_(1,T)(n) and ω_(2,T)(n).Further, and as now discussed and as shown in FIG. 2, the DPCH pilotsymbols y(n) are connected to a channel estimation and beamformerverification block 56. Block 56 also receives as inputs the channelmeasurement values α_(1,n) and α_(2,n) from channel measurement block 50and the phase difference values φ₁(n) and φ₂(n) from beamformercoefficient computation block 52. In response to its inputs, block 56outputs the channel estimation, introduced earlier as ĥ_(n), to MRCblock 23, but in doing so the beamformer verification process attemptsto ensure that ĥ_(n) is correctly estimated in view of previously fedback beamformer coefficients. Specifically, note that ĥ_(n) may bedefined according to the following Equation 4:ĥ _(n)=α_(1,n)ω_(1,T)(n)+α_(2,n)ω_(2,T)(n)  Equation 4Thus, Equation 4 indicates mathematically that the overall change (i.e.,the channel estimation, ĥ_(n)) in a signal received by user station 14should be reflected by both the channel measurement factors α_(1,n) andα_(2,n) as well as the weight factors ω_(1,T)(n) and ω_(2,T)(n) thatwere multiplied by base station 12 against the signal before it wastransmitted by base station 12 to user station 14. Thus, beamformerverification is a process by which user station 14 attempts to ascertainω_(1,T)(n) and ω_(2,T)(n) as used by base station 12, and those valuesmay then be used to determine ĥ_(n).

Equation 4 also demonstrates that, in one approach, the channelestimation, ĥ_(n), could be a direct calculation because block 56receives the channel measurement values α_(1,n) and α_(2,n) and if it isassumed that ω_(1,T)(n) and ω_(2,T)(n) could be identified from thephase difference values φ₁(n) and φ₂(n) from beamformer coefficientcomputation block 52. However, because base station 12 responds to{tilde over (ω)}₂(n) rather than ω₂(n), then beamformer verification isa process by which user station 14 attempts to predict what value of{tilde over (ω)}₂(n) was received by base station 12 and that predictedvalue may then be used to identify the counterpart ω_(2,T)(n) inEquation 4 to determine ĥ_(n). To further appreciate this concept,beamformer verification also may be understood in connection with anexample. Thus, suppose for a slot n=1, user station 14 transmits afeedback value of ω₂(1) to base station 12; in response, base station 12receives a value, {tilde over (ω)}₂(1), block 21 produces acorresponding value ω_(2,T)(1), and a product ω_(2,T)(1)S_(i) is formedand transmitted next to user station 14. Under beamformer verificationas used in the prior art mode 1, user station 14 receives the signalω_(2,T)(1)S_(i), and from that signal it attempts to determine whatvalue of ω_(2,T)(1) was actually used by base station 12 in itscorresponding transmission, and this attempt is achieved by block 56using a methodology referred to as hypothesis testing. This determinedvalue, rather than the actual value ω₂(1) which was fed back by userstation 14, is then used by block 56 to determine ĥ_(n), and that valueof ĥ_(n) is used by MRC block 23 for further signal processing.

Concluding the discussion of the prior art mode 1, note that its use ofonly two possible data values for ω₂(n), in combination with theoperations relating to hypothesis testing, have yielded a workable errorrate at a reasonable level of performance speed. Indeed, relative toprior art modes 2 and 3 described below, the feedback delay of prior artmode 1 is relatively small, and a certain level of performance isachieved given this reduced delay. However, the resulting resolutionobtained in response to the 2-state level of quantization of mode 1 isrelatively low as compared to prior art modes 2 and 3 as furtherdiscussed below.

Looking to the prior art mode 2 of operation from Table 1, it is usedfor relatively mid-level Doppler fading rates, such as would be expectedwhen a particular mobile user station 14 with which base station 12 iscommunicating is moving at a lesser rate of speed than for the case of amode 1 communication. Mode 2 again uses the convention of Equation 1 andnormalizes ω₁(n) (and thereby its counterpart φ₁(n)), but addedresolution is obtained in the computation of φ₂(n) and ω₂(n) bybeamformer coefficient computation block 52. Specifically, block 52 inmode 2 applies a 45 degree constellation rotation per slot to the2-value beamformer coefficient, that is, for each successive slot, φ₂(n)and ω₂(n) are determined based on a 45 degree rotation relative to thepreceding slot; particularly, since a total of four such rotationscorresponds to 180 degrees, then under the 45 degree constellationrotation the slots are generally analyzed by user station 14 by adding a45 degree rotation to each successive slot in each succession of fourslots. This rotation is achieved at user station 14 by determining thevalue of φ₂(n) and ω₂(n) in part based on the time slot in which theslot at issue leas received and then choosing the value of ω₂(n) withrespect to the rotation to be applied to the given slot for a group i offour slots. This rotation is explored immediately below in connectionwith the following Table 2 and is also depicted pictorially in FIG. 4.

TABLE 2 w₂(n) slot 4i slot 4i + 1 slot 4i + 2 slot 4i + 3 0 0 π/4 π/23π/4 1 π −3π/4 −π/2 −π/4

Looking to Table 2 and FIG. 4, for a first slot 4 i in a group i of fourslots, the values of φ₂(n) and ω₂(n), as determined by beamformercoefficient computation block 52 in user station 14, are based on arotation of zero degrees, as shown in graph 60 and as represented by itsaxis 60 _(ax) which is not rotated relative to the vertical imaginaryaxis. More particularly, graph 60 illustrates two shaded areas 60 ₁ and60 ₂, where if the channel measurement α_(2,n) ^(H)α_(1,n) from channelmeasurement block 50 falls within area 60 ₁, then block 52 computes thevalue of φ₂(4 i) to be 0 degrees and this value is encoded to acorresponding binary form ω₂(4 i)=0 by encode block 54 and is fed backto base station 12; conversely, if the channel measurement α_(2,n)^(H)α_(1,n) falls within area 60 ₂, then block 52 computes the value ofφ₂(4 i) to be π radians and this value is encoded to a correspondingbinary form ω₂(4 i)=1 by block 54 and is fed back to base station 12.Further, Table 2 as well as the location of points on graph 60illustrate the phase rotation that is implemented by base station 12 inresponse to the values of {tilde over (ω)}₂(4 i). Specifically, if basestation 12 receives a value of {tilde over (ω)}₂(4 i) equal to 0, thenfeedback decode and process block of base station 12 treats the channelmeasurement phase change for slot 4 i as 0 degrees; however, if basestation 12 receives a value of {tilde over (ω)}₂(4 i) equal to 1, thenbase station 12 treats the channel measurement phase change for slot 4 ias equal to π radians.

Table 2 and FIG. 4 also illustrate the remaining three slots in group i,where comparable reference numbers are used in FIG. 4 such that graph 62corresponds to slot 4 i+1 and represents a rotation equal to π/4radians, graph 64 corresponds to slot 4 i+2 and represents a rotationequal to π/2 radians, and graph 66 corresponds to slot 4 i+3 andrepresents a rotation equal to 3π/4 radians. Thus, looking to graph 62as another example, its axis 62 _(ax) depicts the rotation of π/4radians relative to the vertical imaginary axis as used for slot 4 i+1.Further, graph 62 illustrates two shaded areas 62 ₁ and 62 ₂, where ifthe channel measurement α_(2,n) ^(H)α_(1,n) determined by block 50 ofuser station 14 falls within area 62 ₁, then the value of φ₂(4 i+1) isπ/4 radians and a corresponding binary value for ω₂(4 i+1) equal to 0 isproduced and fed back to base station 12, whereas if the channelmeasurement α_(2,n) ^(H)α_(1,n) falls within area 62 ₂, then the valueof φ₂(4 i+1) is −3π/4 radians and a corresponding binary value for ω₂(4i+1) equal to 1 is produced and fed back to base station 12. Further,Table 2 as well as the location of points on graph 62 illustrate thephase rotation that is implemented by base station 12 in response to thevalues of {tilde over (ω)}₂(4 i+1). Specifically for slot 4 i+1, if basestation 12 receives a value of {tilde over (ω)}₂(4 i+1) equal to 0, thenfeedback decode and process block of base station 12 treats the channelestimation phase change for slot 4 i+1 as π/4 radians; however, if basestation 12 receives a value of {tilde over (ω)}₂(4 i+1) equal to 1, thenbase station 12 treats the channel estimation phase change for slot 4i+1 as equal to −3π/4 radians. Given this second example as well as thepreceding example described above, one skilled in the art should readilyappreciate the remaining values and illustrations in Table 2 and FIG. 4as applied to the value of φ₂(n) by user station 14 and the conversionof that value to ω₂(n) as well as the interpretation of the value of{tilde over (ω)}₂(n) by feedback decode and process block of basestation 12 according to mode 2 in the prior art.

Attention is now directed to an additional aspect of the prior art mode2 processing in response to ω₂(n) transmitted by user station 14. First,recalling the convention introduced above with respect to mode 1, fromthe perspective of base station 12, {tilde over (ω)}₂(n) represents thesignal actually received by base station 12 and corresponding to thefeedback transmission of ω₂(n) from user station 14. Second, note nowthat feedback decode and process block 21 during the prior art mode 2actually uses an averaging filter to determine the value of ω_(2,T)(n)for each received value of {tilde over (ω)}₂(n). Specifically, block 21calculates an average over four values of ω₂ (or {tilde over (ω)}₂, fromthe perspective of base station 12), so that the result is ω_(2,T)(n)and is defined by the following Equation 5:

$\begin{matrix}{{w_{2,T}(n)} = \frac{\begin{matrix}{{{\overset{\sim}{w}}_{2}( {4i} )} + {{\overset{\sim}{w}}_{2}( {{4i} - 1} )} +} \\{{{\overset{\sim}{w}}_{2}( {{4i} - 2} )} + {{\overset{\sim}{w}}_{2}( {{4i} - 3} )}}\end{matrix}}{4}} & {{Equation}\mspace{14mu} 5}\end{matrix}$The indication of {tilde over (ω)}₂(4 i) in Equation 5 is to depict themost recent beamformer coefficient received by base station 12 via thefeedback channel, and thus the remaining three addends in Equation 5 arebased on the three other beamformer coefficients preceding that mostrecent coefficient. These four values are averaged (i.e., divided by 4),and in the prior art mode 2 of operation, base station 12 multiplies theresult, ω_(2,T)(n), times the signal from second output 18 ₂ connectedto multiplier 20 ₂. ω_(1,T)(n), however, is simply the counterpart tothe normalized value ω₁(n), and base station 12 multiplies it times thesignal from first output 18 ₁, connected to multiplier 20 ₁.

Given the preceding, one skilled in the art will appreciate that theprior art mode 2 also implements the feedback of one of two values(i.e., for ω₂(n)). However, given the additional use of phase rotation,greater beamformer resolution is achieved relative to prior art mode 1.In other words, while ω₂(n) for any given slot may only take one of twovalues as in the case of the prior art mode 1, the use of 45 degreerotation over four slots creates an effective constellation of eightpossible values (i.e., 2 values/slot*4 slots/rotation cycle=8 values).However, note that the prior art mode 2 does not use any type ofbeamformer verification which is used by prior art mode 1; indeed, thepresent inventors have observed that beamformer verification may not befeasible for the prior art mode 2 because it could add, in combinationwith the four-cycle 45 degree rotation, an unworkable amount ofcomplexity. Further, with phase rotation and averaging, the betterresolution of the prior art mode 2 is offset in part by an increasedoverall delay relative to prior art mode 1.

Looking to the prior art mode 3 of operation from Table 1, it isappreciated as used for Doppler fading rates that are relatively low ascompared to prior art modes 1 and 2, where the mode 3 fading rates wouldbe expected when mobile user station 14 is moving at a relatively lowrate of speed. Given the lower speed of user station 14, additional timeis available for additional levels of processing, as is implemented inthe prior art mode 3. Specifically, mode 3 increases its quantizationfor the beamformer coefficients, but the increase is not achieved basedon rotation as shown in FIG. 2 for the prior art mode 2. Instead, theprior art mode 3 feeds back a total of four bits of information, whereone bit is intended as an amplitude correction bit while the remainingthree bits are to correct for phase shifts.

Having discussed closed loop transmit antenna diversity system 10 as itmay implement the prior art, the attention is now directed to animplementation of the preferred embodiment into system 10. By way ofoverview to the preferred embodiment, it contemplates variousalternative aspects versus those discussed above. First, in thepreferred embodiment, prior art modes 1 and 2 are eliminated andreplaced by a single mode of operation; because this single mode ofoperation spans the entire Doppler fading range of prior art modes 1 and2, it is hereafter referred to as the broad range closed loop mode.Thus, the broad range dosed loop mode may be combined with the prior artmode 3 of operation to accommodate the entire anticipated range ofDoppler frequencies for closed loop communications. Second, with respectto the broad range closed loop mode, in addition to providing one modein place of two prior art modes, it includes additional aspects thatdistinguish it further from the prior art. One such aspect is the use ofa two phase rotation for determining beamformer coefficients. Anotheraspect is the use of beamformer verification, implemented using one oftwo different alternatives, in the same mode that implements phaserotation for determining beamformer coefficients. Each of these pointsshould be further appreciated by one skilled in the art given theremaining teachings of this document.

The use of a two phase rotation for determining beamformer coefficientsaccording to the broad range closed loop mode is now described. Thebroad range closed loop mode uses the earlier convention from Equation 1and normalizes the value ω₁(n) as detailed later, and also therebynormalizes its phase difference counterpart, φ₁(n); however, in thepreferred embodiment an overall resolution differing from the prior artmodes 1 and 2 is obtained in the computation of φ₂(n) and ω₂(n) bybeamformer coefficient computation block 52. Specifically, block 52 inthe broad range closed loop mode applies a 90 degree constellationrotation per slot to the 2-value beamformer coefficient. Accordingly,for each successive slot n, n+1, n+2, and so forth, φ₂(n) and ω₂(n) aredetermined based on a 90 degree rotation relative to the preceding slot.Since a total of two such rotations correspond to 180 degrees, thenunder the 90 degree constellation rotation the slots are generallyanalyzed by user station 14 by adding a 90 degree rotation to eachsuccessive slot. This rotation is achieved at user station 14 bydetermining the value of φ₂(n) in part based on the time slot in whichthe slot at issue was received and then choosing the value of φ₂(n) withrespect to the rotation to be applied to the given slot for a group i oftwo slots. This rotation is explored immediately below in connectionwith the following Table 3 and is also depicted pictorially in FIG. 5,and recall also that these operations may be implemented within system10 shown in FIG. 1 to thereby create the preferred embodiment.

TABLE 3 w₂(n) slot 2i slot 2i + 1 0 0   π/2 1 π −π/2

Looking to Table 3 and FIG. 5, for a first slot 2 i in a group i of twoslots, the value of φ₂(2 i), as determined by beamformer coefficientcomputation block 52 in user station 14, is based on a rotation of zerodegrees as shown in graph 70 and as represented by its axis 70 _(ax)which is not rotated relative to the vertical imaginary axis. Moreparticularly, graph 70 illustrates two shaded areas 70 ₁ and 70 ₂, whereif the channel measurement α_(2,n) ^(H)α_(1,n) from block 50 fallswithin area 70 ₁, then block 52 computes the value of φ₂(2 i) to be 0degrees and this value is encoded by encode block 54 to produce a binarycounterpart of ω₂(2 i)=0 which is fed back to base station 12;conversely, if the channel measurement α_(2,n) ^(H)α_(1,n) falls withinarea 70 ₂, then block 52 computes the value of φ₂(2 i) to be π radiansand this value is encoded by block 54 to produce a binary counterpart ofω₂(2 i)=1 which is fed back to base station 12. Further, Table 3 as wellas the location of points on graph 70 illustrate the phase rotation thatis implemented by base station 12 in response to the possible values of{tilde over (ω)}₂(2 i). Specifically, if base station 12 receives avalue of {tilde over (ω)}₂(2 i)=0, then feedback decode and processblock of base station 12 treats the channel measurement phase change forslot 2 i as 0 degrees; however, if base station 12 receives a value of{tilde over (ω)}₂(2 i)=1, then base station 12 treats the channelmeasurement phase change for slot 2 i as equal to π radians.

Table 3 and FIG. 5 also illustrate that for a second slot, 2 i+1, in thegroup i of two slots, the value of φ₂(2 i+1), as determined bybeamformer coefficient computation block 52 in user station 14, is basedon a 90 degree rotation as shown in graph 72 and as represented by itsaxis 72 _(ax) which is rotated 90 degrees relative to the verticalimaginary axis. Graph 72 illustrates two shaded areas 72 ₁ and 72 ₂,where if the channel measurement α_(2,n) ^(H)α_(1,n) from block 50 fallswithin area 72 ₁, then block 52 computes the value of φ₂(2 i+1) to beπ/2 radians and this value is encoded by encode block 54 into a binarycounterpart ω₂(2 i+1) equal to 0 which is fed back to base station 12;conversely, if the channel measurement α_(2,n) ^(H)α_(1,n) falls withinarea 72 ₂, then block 52 computes the value of φ₂(2 i+1) to be π/2radians and this value is encoded by block 54 into a binary counterpartω₂(2 i+1) equal to 1 which is fed back to base station 12. Further,Table 3 as well as the location of points on graph 72 illustrate thephase rotation that is implemented by base station 12 in response to thevalues of {tilde over (ω)}₂(2 i+1). Specifically, if base station 12receives a value of {tilde over (ω)}₂(2 i+1) equal to 0, then feedbackdecode and process block of base station 12 treats the channelmeasurement phase change for slot 2 i+1 as π/2 radians; however, if basestation 12 receives a value of {tilde over (ω)}₂(2 i+1) equal to 1, thenbase station 12 treats the channel measurement phase change for slot 2 ias equal to −π/2 radians.

The preceding operations of the broad range closed loop mode todetermine the value of ω₂(n) also may be represented mathematically byrelating to the actual phase difference value φ(n) from Table 3 (i.e.,one of the values 0, π, π/2, or −π/2). In this case, then in thepreferred embodiment and for a slot n, φ(n) is chosen to maximize theinstantaneous power, P(n), defined according to the following Equation6:

$\begin{matrix}{{P(n)}^{def} = {{{{\alpha_{1,n}{\omega_{1}(n)}} + {\alpha_{2,n}{\omega_{2}(n)}}}}^{2} = {\frac{1}{2}( {{\alpha_{1,n}}^{2} + {\alpha_{2,n}}^{2} + {2 \times {real}\{ {\alpha_{1,n}^{H}\alpha_{2,n}{\mathbb{e}}^{j\;{\phi_{2}{(n)}}}} \}}} )}}} & {{Equation}\mspace{14mu} 6}\end{matrix}$Equation 6 implements various conventions which are now defined forclarity. First, real{x} denotes the real portion of a complex number x.Second, the superscript of “H” denotes the conjugate of a matrix orvector transpose. Finally, ∥v∥ denotes the Euclidean norm of vector v.

Further in the preferred embodiment, and as may be seen from Equation 6,the maximum of the instantaneous power, P(n), occurs where φ₂(n) is atsuch a value so as to maximize the term from Equation 6 of real{α_(1,n)^(H)α_(2,n)e^(jφ) ² ^((n))} with φ(n)∈{0,π} when n is even, andφ(n)∈{±π/2} when n is odd. Thus, under the preferred embodiment, thevalue of φ₂(n) may be selected to be of two values, for either n beingodd or even, by reference only to the term real{α_(1,n)^(H)α_(2,n)e^(jφ) ² ^((n))}, as is achieved by the block diagram in FIG.6. Specifically, FIG. 6 illustrates a block diagram which achieves thisresult and that combines beamformer coefficient computation block 52 andbeamformer coefficient binary encode block 54 from FIG. 2; further, forsake of reference, the combined block of FIG. 6 is hereafter referred toas block 52/54. The blocks are combined because the diagram in FIG. 6both implements the determination of the phase difference φ₂(n)represented in Equation 6 above and also encodes that difference intobinary form, that is, into the corresponding value of ω₂(n). Lastly, byway of contrast, note that one approach in the prior art to computing aphase difference to maximize instantaneous power is achieved simply by alook-up table, but as will be appreciated below the preferred embodimentprovides a less complex alternative to such an approach.

Looking to FIG. 6, the values α_(1,n) and α_(2,n) from channelmeasurement block 50 are input to the combined block 52/54.Specifically, these values are coupled to inputs 80 ₁ and 80 ₂ of acomplex dot product block 80. Block 80 represents the function ofdetermining the complex dot product of the values provided at its inputs80 ₁ and 80 ₂. Thus, for the instance shown in FIG. 6, this product isas shown at the output 80 ₃ of block 80, and is also shown in thefollowing Equation 7:output 80₃=α_(1,n) ^(H)α_(2,n)  Equation 7Thus, block 80, as also shown by Equation 7, yields the product of thefirst two multiplicands in the term real{α_(1,n) ^(H)α_(2,n)e^(jφ) ²^((n))} from Equation 6.

The dot product output from complex dot product block 80 is coupled toan alternating switch 82. Switch 82 toggles to a first position for oneslot, and then to a second position for the next slot; specifically, fora first slot 2 i in a group of i slots, switch 82 connects the output ofcomplex dot product block 80 to a real component extraction block 84 andso that for a second slot 2 i+1 in the group of i slots, switch 82connects the output of complex dot product block 80 to an imaginarycomponent extraction block 86.

Real component extraction block 84 operates to select and output onlythe real portion of the value provided at its input, and conversely,imaginary component extraction block 86 outputs only the imaginaryportion of the value provided at its input. The output of real componentextraction block 84 is coupled to a decision block 88 which also may bea comparator or comparing function, where if the real component fromblock 84 is greater than or equal to zero, then a block 90 is reached,while in contrast if the real component from block 84 is less than zero,then a block 92 is reached. The output of imaginary component extractionblock 86 is coupled to a decision block 94 which may be a comparator orcomparing function, where if the imaginary component from block 86 isless than or equal to zero, then a block 96 is reached, while incontrast if the imaginary component from block 86 is greater than zero,then a block 98 is reached.

The ultimate results produced by the operation of block 52/54 may beappreciated by one skilled in the art given the assignment of valuesshown in FIG. 6 in blocks 90, 92, 96 and 98. For a slot n=2 i, it isshown later that decision block 88 directs the flow to either block 90or block 92 based on the maximization of the term real{α_(1,n)^(H)α_(2,n)e^(jφ) ² ^((n))} from Equation 6 for φ₂(n)∈{0,π}, and each ofthose two blocks 90 and 92 assigns to φ₂(n) one of the two differentvalues shown in Table 3 for n=2 i(i.e., 0 or π, respectively). Block 90and block 92 also encode the value assigned to φ₂(n) into acorresponding binary counterpart ω₂(n), as also shown in Table 3. Also,for a slot n=2 i+1, it is shown later that decision block 94 directs theflow to either block 96 or block 98 based on the maximization of theterm real{α_(1,n) ^(H)α_(2,n)e^(jφ) ² ^((n))} from Equation 6 forφ₂(n)∈{±π/2}, and each of those two blocks 96 and 98 assigns to φ₂(n)one of the two different values shown in Table 3 for n=2 i+1 (i.e., π/2or −π/2, respectively). Block 96 and block 98 also encode the valueassigned to φ₂(n) into a corresponding binary counterpart ω₂(n), as alsoshown in Table 3. Finally, note that the assigned values from any ofblocks 90, 92, 96, and 98 are provided to the blocks shown in FIG. 2,that is, the value of ω₂(n) is fed back to base station 12 while thevalue of φ₂(n) is coupled to beamformer verification block 56.

An additional appreciation of the operation of block 52/54 with respectto the extraction of a real component by block 84 is now explored instill further detail, and from this discussion one skilled in the artshould appreciate the additional benefits realized by the particularimplementation of FIG. 6. Generally, real component extraction block 84,in combination with decision block 88, determines the value of φ₂(n)that maximizes instantaneous power, P(n), by taking advantage of certaincomplex arithmetic identities. In operating in this fashion, theseblocks provide an architecture requiring less complexity than othercomputational or storage-intensive techniques. Blocks 84 and 88 dealwith the case where φ₂(n)∈{0,π}. Looking further at the implications ofthese two values for φ₂(n), note that with respect to the finalmultiplicand in the real portion of Equation 6 they produce the resultsshown in Equations 8 and 9:e^(j0)=1  Equation 8e ^(jπ)=−1  Equation 9From Equations 8 and 9, it should be appreciated that to maximize P(n),the value of φ₂(n) must be such that the result of real{α_(1,n)^(H)α_(2,n)e^(jφ) ² ^((n))} is positive. For example, if real{α_(1,n)^(H)α_(2,n)} is a positive value, then as between the two multiplicandsfrom Equations 8 and 9, P(n) would be maximized by multiplying it timesthe resulting multiplicand of 1 from Equation 8, and indeed decisionblock 88 passes flow to block 90 in this case to thereby assign thevalue of 0 degrees to φ₂(n) because that value therefore maximizes P(n).As another example, if real{α_(1,n) ^(H)α_(2,n)} is a negative value,then P(n) would be maximized by multiplying it times the resultingmultiplicand of −1 from Equation 9 to form a positive value product, andindeed decision block 88 passes flow to block 92 in this case to therebyassign the value of π radians to φ₂(n) because that value thereforemaximizes P(n). In either case, therefore, blocks 88, 90, and 92 yieldthis determination without requiring the additional complexity of havingto perform an actual multiplication times e^(jθ).

An additional appreciation of the operation of block 52/54 with respectto the extraction of an imaginary component by block 86 is also nowexplored in still further detail, and from this discussion one skilledin the art should appreciate the additional benefits realized by theparticular implementation of FIG. 6. Imaginary component extractionblock 86 operates in combination with decision block 94, again todetermine the value of φ₂(n) that maximizes instantaneous power, P(n),and also by taking advantage of certain complex arithmetic identities.Once more, therefore, an embodiment is provided that requires lesscomplexity than other more computational or storage-intensivetechniques. Blocks 86 and 94 deal with the case where φ₂(n)∈{π/2,−π/2}.Looking further at the implications of these two values for φ₂(n), notethat with respect to the final multiplicand e^(jφ2(n)) in the realportion of Equation 6 they produce the following results shown inEquations 10 and 11:e ^(j(π/2))=j  Equation 10e ^(j(−π/2))=−j  Equation 11Both Equations 10 and 11 produce imaginary results, and it is observedin connection with the preferred embodiment that these results, ifmultiplied times the real value in Equation 6, would have asign-detectable effect on the imaginary portion of the result, asfurther appreciated from the following complex arithmetic principles.Again, to maximize P(n), the value of φ₂(n) must be such that the resultof real{α_(1,n) ^(H)α_(2,n)e^(jφ) ² ^((n))} is positive. However, in thecase for slot 2 i+1 where φ₂(n)∈{π/2,−π/2}, and as shown in Equations 10and 11, the value real{α_(1,n) ^(h)α_(2,n)e^(jφ) ² ^((n))} includes thedot product from block 80 and multiplied times either j or −j. Further,the following Equations 12 through 15 demonstrate additional complexarithmetic principles that facilitate an understanding of blocks 86 and94, where v and y are complex numbers and are multiplied times either jor −j as shown:v(j)=(a+jb)(j)=aj+j ² b=aj−b  Equation 12v(−j)=(a+jb)(−j)=−aj−j ² b=−aj+b  Equation 13y(j)=(c−jd)j=cj−j ² d=cj+d  Equation 14y(−j)=(c−jd)(−j)=−cj+j ² d=−cj−d  Equation 15Given the preceding, and again with the goal of maximizing P(n),Equations 12 through 15 demonstrate the following observations. Equation13 versus Equation 12 demonstrates a larger real portion in the Equation13 complex number product (i.e., b versus −b, making b the maximum ofthe two), and the two Equations further demonstrate that to achieve theresult having a larger real portion, for a complex number with apositive imaginary value (i.e., b), then the complex number must bemultiplied times −j. Thus, in the context of FIG. 6, if the complex dotproduct from block 80 has a positive imaginary value (which is extractedby block 86), then the product real{α_(1,n) ^(H)α_(2,n)e^(jφ) ² ^((n))}is maximized when multiplied times −j, which occurs when φ₂(n)=−π/2;indeed decision block 94 passes flow to block 98 in this case to therebyassign the value of −π/2 radians to φ₂(n). Conversely, Equation 14versus Equation 15 demonstrates a larger real portion in the Equation 14complex number product (i.e., d versus −d), and the two Equationsfurther demonstrate that to achieve this maximum result, for a complexnumber with a negative imaginary value (i.e., d), then the complexnumber must be multiplied times j. Thus, in the context of FIG. 6, ifthe complex dot product from block 80 has a negative or zero imaginaryvalue (which is extracted by block 86), then the product real{α_(1,n)^(H)α_(2,n)e^(jφ) ² ^((n))} is maximized when multiplied times j, whichoccurs when φ₂(n)=π/2; indeed decision block 94 passes flow to block 96in this case to thereby assign the value of π/2 radians to φ₂(n). Ineither event, therefore, a proper value of φ₂(n) is assigned to maximizeP(n), and again without requiring the additional complexity of having toperform an actual multiplication times e^(jθ).

Returning now to base station 12, a further discussion is provided ofthe broad range closed loop mode in response to a closed loop value (orvalues) fed back from user station 14. Recall first the above-introducedconventions, that is, user station 14 feeds back the value of ω₂(n) (andω₁(n) if it is not normalized), but this fed back value undergoes thechannel effects in the feedback channel so that the corresponding valueactually received by base station 12 is designated {tilde over (ω)}₂(n).Given this value, feedback decode and process block 21 provides a twostep operation, and for sake of simplification each of these steps isdiscussed separately below.

As a first operation of block 21 and in response to {tilde over(ω)}₂(n), block 21 determines an actual phase difference, designated asφ_(2,T)(n), corresponding to {tilde over (ω)}₂(n); this determination isachieved by the mapping of Table 3. In other words, if for slot n=2 i,{tilde over (ω)}₂(2 i) equals a binary value of 0, then block 21determines that φ_(2,T)(2 i) equals 0 degrees, whereas if {tilde over(ω)}₂(2 i) equals a binary value of 1, then block 21 determines thatφ_(2,T)(2 i) equals π radians. Additionally, if for slot ,n=2 i+1,{tilde over (ω)}₂(2 i+1) equals a binary value of 0, then block 21determines that φ_(2,T)(2 i+1) equals π/2 radians, whereas if {tildeover (ω)}₂(2 i+1) equals a binary value of 1, then block 21 determinesthat φ_(2,T)(2 i+1) equals −π/2 radians.

A second operation of block 21 is in response to the determined value ofφ_(2,T)(n) described immediately above. Specifically, having receivedthe value φ_(2,T)(n), block 21 determines the actual multiplicands to beused multipliers 20 ₁ and 20 ₂. Recalling that ω_(1,T)(n) is normalized,in the preferred embodiment its actual normalized value as to be used bymultiplier 18 ₁ is as set forth in the following Equation 16:

$\begin{matrix}{{w_{1,T}(n)} = \frac{1}{\sqrt{2}}} & {{Equation}\mspace{14mu} 16}\end{matrix}$Of course, since the Equation 16 value is constant, it may be providedonly once by calculation or, indeed, it may be fixed in some storageelement or the like. Looking to ω_(2,T)(n), however, it is based on theactual value of φ_(2,T)(n) as determined above by block 21; moreover, inthe preferred embodiment, the value of ω_(2,T)(n) is based on an averageof two received values of φ_(2,T) corresponding to two successive slots,that is, with respect to φ_(2,T)(n) and φ_(2,T)(n−1), as further setforth in the following Equation 17:

$\begin{matrix}{{w_{2,T}(n)} = {\frac{1}{2}( {{\mathbb{e}}^{j\;{\phi_{2}{(n)}}} + {\mathbb{e}}^{j\;{\phi_{2}{({n - 1})}}}} )}} & {{Equation}\mspace{14mu} 17}\end{matrix}$Indeed, the two-slot averaging approach represented by Equation 17demonstrates that the preferred embodiment reduces computationalcomplexity and delay of the four-slot averaging approach implemented inconnection with the prior art (e.g., Equation 5). Further, for purposesof analysis and discussion, the two addends within parenthesis ofEquation 17 represent an addition in the complex plane and, thus, thefollowing term may be defined with respect to Equation 17 to introduce arelated factor of θ_(T)(n):

$\begin{matrix}{{w_{2,T}(n)} = {{\frac{1}{2}( {{\mathbb{e}}^{j\;{\phi_{2}{(n)}}} + {\mathbb{e}}^{j\;{\phi_{2}{({n - 1})}}}} )^{def}} = {\frac{1}{\sqrt{2}}{\mathbb{e}}^{j\;{\theta_{T}{(n)}}}}}} & {{Equation}\mspace{14mu} 18}\end{matrix}$Thus, Equation 18 defines θ_(T)(n) as the average of two received valuesof φ_(2,T) corresponding to two successive slots; further, because foran even slot n, {circumflex over (φ)}_(2,T)(n)∈{0,π}, and for an oddslot n,

${{{\hat{\phi}}_{2,T}(n)} \in \{ {\frac{\pi}{2},\frac{- \pi}{2}} \}},$then the average between any one value from even slot n and animmediately preceding odd slot n−1 can take only one of four values,that is,

${\theta_{T}(n)} \in {\{ {\frac{\pi}{4},\frac{3\;\pi}{4},\frac{{- 3}\;\pi}{4},\frac{- \pi}{4}} \}.}$Further, given the results of Equations 17 and 18, the values ofω_(1,T)(n) and ω_(2,T)(n) are used by multipliers 20 ₁ and 20 ₂,respectively, thereby producing signals ω_(1,T)(n)S_(i) andω_(2,T)(n)S_(i), which are transmitted by antennas A12 ₁ and A12 ₂,respectively, to user station 14.

With base station 12 having transmitted the signals ω_(1,T)(n)S_(i) andω_(2,T)(n)S_(i) to user station 14 and according to the preferred broadrange closed loop mode, attention is now further directed to thepreferred beamformer verification by user station 14, as implemented ina preferred embodiment for channel estimation and beamformerverification block 56. Recall from the earlier introduction ofbeamformer verification that it arises from the recognition that atransmission by base station 12 may implement a weight value (e.g.,ω_(2,T)(n)) that is influenced by feedback channel effects, andbeamformer verification in general is an attempt by user station 14 toascertain the actual weight value used by base station 12. Theascerained value is then usable by user station 14 to determine thevalue of ĥ_(n) to be used for maximal ratio combining in block 23.Further, in the preferred embodiment beamformer verification may beimplemented using one of two different alternatives in the broad rangeclosed loop mode. Each of these alternatives is discussed later.

FIG. 7 illustrates a block diagram of channel estimation and beamformerverification block 56 in greater detail and it is now explored furtherin connection with the preferred embodiment. Recall from earlier thatblock 56 receives various inputs from other blocks in FIG. 2, includingthe values of the DPCH pilot symbols y(n) from pilot symbol extractor 44and the phase difference values φ₁(n) and φ₂(n) from beamformercoefficient computation block 52 (or just φ₂(n) if φ₁(n) is normalized).As detailed further in FIG. 7, these inputs are coupled to a beamformerverification block 100. Further, block 56 also receives as inputs thechannel measurement values α_(1,n) and α_(2,n) from channel measurementblock 50, where the value α_(1,n) is connected as an input to a firstmulti-slot averaging estimator 102 while the value α_(2,n) is connectedas an input to a second multi-slot averaging estimator 104. The outputsof estimators 102 and 104 provided estimates corresponding to the inputvalues α_(1,n) and α2 _(2,n), and for sake of convention these estimatesare identified as {circumflex over (α)}_(1,n) and {circumflex over(α)}_(2,n). The estimates {circumflex over (α)}_(1,n) and {circumflexover (α)}_(2,n) are connected as input multiplicands to respectivemultipliers 106 and 108, and the estimate {circumflex over (α)}_(2,n) isalso connected as an input to beamformer verification block 100. Theoutput of beamformer verification block 100 is the estimate by userstation 14 of the value ω_(2,T)(n) used by base station 12, and for sakeof reference, this output is identified as {circumflex over(ω)}_(2,T)(n). The value {circumflex over (ω)}_(2,T)(n) is alsoconnected as a second input multiplicand to multiplier 108, while thevalue of {circumflex over (ω)}_(1,T)(n), shown in FIG. 7 as the constantfrom Equation 16, above, is connected as a second input multiplicand tomultiplier 106. The product output of multipliers 106 and 108 arecoupled to a adder 110, and which has an output that provides ĥ_(n) toMRC block 23. Finally, the operation of channel estimation andbeamformer verification block 56 is described below.

Estimators 102 and 104 refine the channel measurements provided asinputs to those estimators. In the preferred embodiment, each ofestimators 102 and 104 computes a multi-slot average of its inputs toprovide what is anticipated as a more accurate estimate, therebyrepresented as {circumflex over (α)}_(1,n) and {circumflex over(α)}_(2,n). Preferably, the multi-slot averaging technique used is theWeighted Multi-Slot Averaging technique known in the art which averagessix slots for low to moderate channel fading rate with the weighting[0.3, 0.8, 1, 1, 0.8, 0.3], and four slots for high fading rate with theweighting [0.6, 1, 1, 0.6].

To appreciate the operation of the remaining blocks and items in block56, first Equations 16 and 18 are substituted into Equation 4 to definethe channel estimation in the form of the following Equation 19:

$\begin{matrix}{{\hat{h}}_{n} = {\frac{1}{\sqrt{2}}( {\alpha_{1,n} + {{\mathbb{e}}^{j\;{\theta_{T}{(n)}}}\alpha_{2,n}}} )}} & {{Equation}\mspace{14mu} 19}\end{matrix}$

Given Equation 19, the values therein for α_(1,n) and α_(2,n) may besatisfied using the refined estimates, {circumflex over (α)}_(1,n) and{circumflex over (α)}_(2,n) from estimators 102 and 104, respectively.The operation of block 56 also endeavors to determine θ_(T)(n) tocomplete the determination of ĥ_(n), and in the preferred embodimentthis operation is achieved by beamformer verification block 100 inresponse to the value of the DPCH pilot symbols, y(n). First in thisregard, note that in the preferred embodiment the pilot symbols, whichrecall differ for each of the different transmit antennas A12 ₁ and A12₂ are orthogonal with respect to one another. Second, in the preferredembodiment beamformer verification block 100 may operate in one of twodifferent alternative methods for determining θ_(T)(n) in response tothe orthogonal DPCH pilot symbols. Generally introducing these twoalternatives, a first may be referred to as a two rotating hypothesistesting method, while a second may be referred to as a four hypothesissingle shot testing method. Each alternative is separately discussedbelow.

Since both preferred beamformer verification methods determine θ_(T)(n)in response to the orthogonal DPCH pilot symbols, y(n), it is noted thatsuch symbols may be written according to the following Equation 20:

$\begin{matrix}{{y(n)} = {{\frac{1}{\sqrt{2}}( {{b_{1}(n)} + {{\mathbb{e}}^{j\;{\theta_{T}{(n)}}}{b_{2}(n)}}} )} + {\psi(n)}}} & {{Equation}\mspace{14mu} 20}\end{matrix}$In Equation 20, ψ(n) is a zero mean complex Guassian noise factor withper component variance of σ². Further, the vector b in Equation 20 isdefined relative to α_(1,n) and α_(2,n) received by block 100 fromestimator 104, and it may be written as in the following Equation 21:

$\begin{matrix}{{b_{k}(n)}^{def} = \begin{bmatrix}\begin{matrix}{{d_{k}(1)}\alpha_{k,n}} \\\vdots\end{matrix} \\{{d_{k}( N_{Y} )}\alpha_{k,n}}\end{bmatrix}} & {{Equation}\mspace{14mu} 21}\end{matrix}$In Equation 21, {d_(k)(1), . . . ,d_(k)(N_(Y))} is the DPCH pilotpattern for antenna k, and N_(Y) is the number of pilot symbols perslot. Further, while Equations 20 and 21 (and others) provide idealsolutions, in providing a preferred embodiment implementation theestimate values may be used therein, such as through the use of{circumflex over (α)}_(2,n) in place of its ideal counterpart α_(2,n).

Finally, therefore, the beamformer verification is chosen by thepreferred embodiment to maximize the aposteriori detecting probability,which as applied to Equation 21 may be represented generally by thefollowing Equation 22:

$\begin{matrix}{\max\limits_{m \in M}( {{\sqrt{2} \times {real}\{ {{y^{H}(n)}{b_{2}(n)}{\mathbb{e}}^{j\;{\hat{\phi}}^{(m)}}} \}} + {\mu(m)}} )} & {{Equation}\mspace{14mu} 22}\end{matrix}$where m is the indexing, M∈{1,2} is the index set of the allowable{circumflex over (φ)}^((m)) values, μ(m) is a threshold parameterdepending upon m. For n=2 i, {circumflex over (φ)} ⁽¹⁾=0 and {circumflexover (φ)}⁽²⁾=π, and for n=2 i+1,

${\hat{\phi}}^{(1)} = {{\frac{\pi}{2}\mspace{14mu}{and}\mspace{14mu}{\hat{\phi}}^{(2)}} = {\frac{- \pi}{2}.}}$

FIG. 8 illustrates a block diagram of a first implementation of abeamformer verification block 100 ₁ that may be readily implemented asbeamformer verification block 100 from FIG. 7, and which operatesaccording to a two rotating hypothesis testing method detailed later. Byway of introduction, block 100 ₁ provides an estimated value designated{circumflex over (ω)}_(2,T)(n), which relates as shown below to thevalue {circumflex over (φ)}^((m)) in Equation 22. Further, the value of{circumflex over (ω)}_(2,T)(n) is, in effect, a prediction by userstation 14 of what was used by base station 12 for a given slot n as itsvalue for ω_(2,T)(n) to weight its signal before it was transmitted touser station 14.

Looking to FIG. 8 in greater detail, it includes a vector formationblock 112 that determines the vector elements of b₂(n) according to theproduct of each pilot data and the appropriate channel estimate α_(k,n)as shown in Equation 21, but note with respect to the value α_(k,n) thatblock 112 actually uses the refined value, {circumflex over (α)}_(2,n),provided by multi-slot averaging estimator 104. The vector b₂(n)determined by block 112 is output as a multiplicand to an input 114 ₁ ofa complex dot product block 114, which receives at another input 114 ₂an additional multiplicand of the vector y(n) from DPCH pilot symbolextractor 44. Block 114 represents tile function of determining thecomplex dot product of the values provided at its inputs 114 ₁ and 114₂. Thus, for the instance shown in FIG. 8, this product is as shown atthe output 114 ₃ of block 114, and is also shown in the followingEquation 23:output 114₃ =y ^(H)(n)b ₂(n)  Equation 23Thus, block 114, as also shown by Equation 23, yields the product of thefirst two multiplicands in the termreal{y^(H)(n)b₂(n)e^(j{circumflex over (φ)}) ^((m)) } from Equation 22.

The product output from complex dot product block 114 is coupled to analternating switch 116. Switch 116 toggles to a first position for thefirst slot 2 i in a group of i slots, thereby connecting the output 114₃ of complex dot product block 114 to a real component extraction block118, and switch 116 toggles to a second position for the second slot 2i+1, thereby connecting the output 114 ₃ of complex dot product block116 to an imaginary component extraction block 120.

Real component extraction block 118 operates to select and output onlythe real portion of the value provided at its input, and this realportion is provided as an addend to a first input 122 ₁ of an adder 122,while the second input 122 ₂ of adder 122 receives a threshold valuedesignated κ_(even) from a threshold block 124. The output 122 ₃ ofadder 122 is connected to a decision block 126 which may be a comparatoror comparing function, where if the sum from output 122 ₃ is greaterthan or equal to zero, then a block 128 is reached, while in contrast ifthe sum is less than zero, then a block 130 is reached. Blocks 128 and130 each assign a phase different value to {circumflex over(φ)}_(2,T)(n) as shown in FIG. 8 (i.e., 0 and π, respectively), and thatvalue is output to a two-slot averaging block 132. The output oftwo-slot averaging block 132 is the final value {circumflex over(ω)}_(2,T)(n) output by block 100 ₁, and is connected in the mannershown and described above relative to FIG. 7.

Imaginary component extraction block 120 operates to select and outputonly the imaginary portion of the value provided at its input, and thisimaginary portion is provided as an addend to a first input 134 ₁ of anadder 134, while the second input 134 ₂ of adder 134 receives athreshold value designated κ_(odd) from threshold block 124. The output134 ₃ of adder 134 is connected to a decision block 136 which may be acomparator or comparing function, where if the sum from output 134 ₃ isless than or equal to zero, then a block 138 is reached, while incontrast if the sum is greater than zero, then a block 140 is reached.Blocks 138 and 140 each assign a phase different value to {circumflexover (φ)}_(2,T)(n) as shown in FIG. 8 (i.e., π/2 or −π/2, respectively),and that value is output to two-slot averaging block 132.

Threshold block 124 provides the threshold values κ_(even) and κ_(odd)to adders 122 and 134, respectively, as introduced above. The followingdiscussion explores the generation of these values, while the effect inresponse to them is discussed later in the overall operation of block100 ₁. With respect to the generation of these values, note thefollowing four observations. First, the subscripted identifiers of“even” and “odd” for the threshold values corresponds to the slot beinganalyzed by block 100 ₁, that is, whether the value of n is an evennumber (e.g., 2 i) or the value of n is an odd number (e.g., 2 i+1).Thus, κ_(even) is determined and used for slots where n is an evennumber, and κ_(odd) is determined and used for slots where n is an oddnumber. Second, recall that beamformer coefficient computation block 52provides the computed phase difference value φ₂(n) to beamformerverification block 100, and which is shown as an input to thresholdblock 124 in FIG. 8. In effect, therefore, threshold block 124 has astored phase difference value corresponding to what user station 14 lastfed back to base station 12. Third, user station 14 includes any one ormore of various algorithms known in the art whereby user station 14 willhave some measure of feedback error rate as a measure between 0 and 1,and which in this document is represented as ε (i.e., ε∈(0,1)). Fourth,as should be understood from the following, κ_(even) is the aprioriprobability of occurrence for ω_(2,n)∈{0,π} in view of φ₂(n) from block52, while κ_(odd) is the apriori probability of occurrence for

$\omega_{2,n} \in \{ {\frac{\pi}{2},\frac{- \pi}{2}} \}$in view of φ₂(n) from block 52.

Given the preceding, κ_(even) and κ_(odd) are determined by thresholdblock 124 according to the following Equations 24 and 25.

$\begin{matrix}{\kappa_{even} = {\frac{{\hat{\sigma}}^{2}}{2\sqrt{2}}\ln\mspace{11mu}{\rho_{even}( {\phi_{2}(n)} )}}} & {{Equation}\mspace{14mu} 24} \\{\kappa_{odd} = {\frac{{\hat{\sigma}}^{2}}{2\sqrt{2}}\ln\mspace{11mu}{\rho_{odd}( {\phi_{2}(n)} )}}} & {{Equation}\mspace{14mu} 25}\end{matrix}${circumflex over (σ)}² in Equations 24 and 25 is the estimate of noisevariance σ², as defined above in connection with Equation 20. Further,the natural logarithms in Equations 24 and 25 are based on the functionsof ρ_(even)(φ(n)) and ρ_(odd)(φ(n)), respectively, and those functionsare defined according to Equation 26 through 29, which how each functionvalue is based on the value of φ₂(n) received by threshold block 124from block 52.

$\begin{matrix}{{\rho_{even} = \frac{1 - ɛ}{ɛ}},{{{for}\mspace{14mu}{\phi_{2}(n)}} = 0}} & {{Equation}\mspace{14mu} 26} \\{{\rho_{even} = \frac{ɛ}{1 - ɛ}},{{{for}\mspace{14mu}{\phi_{2}(n)}} = \pi}} & {{Equation}\mspace{14mu} 27} \\{{\rho_{odd} = \frac{1 - ɛ}{ɛ}},{{{for}\mspace{14mu}{\phi_{2}(n)}} = \frac{- \pi}{2}}} & {{Equation}\mspace{14mu} 28} \\{{\rho_{odd} = \frac{ɛ}{1 - ɛ}},{{{for}\mspace{14mu}{\phi_{2}(n)}} = \frac{\pi}{2}}} & {{Equation}\mspace{14mu} 29}\end{matrix}$The overall operation of block 100 ₁ is now explored. Generally, block100 ₁ determines which of the four constellation values, that is, for aneven slot n, {circumflex over (φ)}_(2,T)(n)∈{0,π}, and for an odd slotn,

${{{\hat{\phi}}_{2,T}(n)} \in \{ {\frac{\pi}{2},\frac{- \pi}{2}} \}},$produces the solution to Equation 22, that is, the maximum value, andfrom Equation 21, it is readily appreciated that this maximum relates tothe dot product of: (1) the DPCH pilot symbols (i.e., y(n)); and (2) theproduct of the refined channel estimates (i.e., {circumflex over(α)}_(2,n), derived by averaging and in response to the PCCPCH pilotsymbols) times the PCCPCH pilot symbols. The following operation ofblock 100 ₁, and as appreciated given its comparable nature to some ofthe operation of FIG. 6, extracts real or imaginary portions of this dotproduct and determines for which value of φ₂(n) a maximum would beobtained if that value were multiplied times the dot product. Asappreciated from the following operational description, however, thisapproach reduces the overall arithmetic complexity by initially nottreating the aspect that, as discussed above, when ω_(2,T)(n) isdetermined by feedback decode and process block 21 according to thepreferred embodiment, it is an average in response to two successivefeedback values, as also shown in Equation 17. Given this introduction,the operation of switch 116 is such that for each even slot, that is, nas an even number (e.g., 2 i), then only the two constellation values{0, π} are considered, where for each odd slot, that is, n as an oddnumber (e.g., 2 i+1), then only the two constellation values {π/2, −π/2}are considered. Further, some of the reduction in complexity is achievedusing complex number principles described earlier in connection withFIG. 6 and, thus, the reader is assumed familiar with that discussionand it is not repeated in considerable detail in connection with FIG. 8.

The operation of real component extraction block 118 of block 100 ₁ andthe response to its output is now described, and is shown to determinean estimated value {circumflex over (φ)}_(2,T)(n) that yields a maximumresult for Equation 22. Real component extraction block 118 and theblocks associated with its output deal with the case where n is even,and {circumflex over (φ)}_(2,T)(n)∈{0,π}. This extracted real portion isthen summed by adder 122 with a threshold from threshold block 124 ofκ_(even) because n is even, and from the previous discussion of thecalculation of κ_(even) one skilled in the art should appreciate thatκ_(even) is a non-zero number. This resulting sum is provided by output122 ₃ to decision block 126. Decision block 126 directs the flow in amanner that may be appreciated from the earlier discussion of Equations8 and 9. Specifically, from Equations 8 and 9 it should be appreciatedthat the two alternatives to which block 126 may direct the value of{circumflex over (φ)}_(2,T)(n), namely, {circumflex over (φ)}_(2,T)(n)=0or {circumflex over (φ)}_(2,T)(n)=π, provide either a multiplicand of 1or −1, respectively, for the term e^(j{circumflex over (φ)}) ^(m) inEquation 22. Thus, if the portion of the product in Equation 22 otherthan the term e^(j{circumflex over (φ)}) ^(m) inreal{y^(H)(n)b₂(n)e^(j{circumflex over (φ)}) ^((m)) }, plus the κ_(even)threshold from block 124, is positive, then a maximum of Equation 22 isrealized if that sum is multiplied times the multiplicand of 1 whichcorresponds to the case of {circumflex over (φ)}_(2,T)(n)=0, and thissolution is realized when decision block 126 detects thatreal{y^(H)(n)b₂(n)} is positive, and directs the flow to block 128 whichthereby assigns a value of 0 degrees to {circumflex over (φ)}_(2,T)(n).Alternatively, if the portion of the product in Equation 22 other thanthe term e^(j{circumflex over (φ)}) ^((m)) inreal{y^(H)(n)b₂(n)e^(j{circumflex over (φ)}) ^((m)) }, plus the κ_(even)threshold from block 124, is negative, then a maximum of Equation 22 isrealized if that remainder is multiplied times the multiplicand of −1which corresponds to the case of {circumflex over (φ)}_(2,T)(n)=π, andthis solution is realized when decision block 126 detects thatreal{y^(H)(n)b₂(n)} is negative and directs the flow to block 130 whichthereby assigns a value of π radians to {circumflex over (φ)}_(2,T)(n).From the preceding, one skilled in the art should appreciate thatEquation 22 is generally maximized by block 100 ₁ when n is even, butwith the added aspect that the feedback error rate, ε, also maydetermine in part the determination of {circumflex over (φ)}_(2,T)(n).Specifically as to the latter, one skilled in the art may confirm thatwhen ε is relatively low then there is a greater likelihood that{circumflex over (φ)}_(2,T)(n) will be assigned to be the same value ofφ₂(n) as earlier determined by block 52, and provided by block 52 toblock 100 ₁. Finally, note also that blocks 118, 126, 128, and 130 yielda solution to Equation 22 without requiring the additional complexity ofhaving to perform an actual multiplication times e^(jθ).

The operation of imaginary component extraction block 120 and theresponse to its output is now described, and it too determines a valueof {circumflex over (φ)}_(2,T)(n) that yields an estimated maximumresult for Equation 22. Imaginary component extraction block 120 and theblocks associated with its output deal with the case where n is odd, and

${{\hat{\phi}}_{2,T}(n)} \in {\{ {\frac{\pi}{2},\frac{- \pi}{2}} \}.}$The extracted imaginary portion is summed by adder 134 with a thresholdfrom threshold block 124 of κ_(odd) because n is odd, and κ_(odd), likeκ_(even), is also a non-zero number that may shift the extractedimaginary portion from block 120 in response to the sign and magnitudeof κ_(odd). The resulting sum from adder 134 is provided by its output134 ₃ to decision block 134, which directs the flow in a manner that maybe appreciated from the earlier discussion of Equations 10 and 11.Specifically, from Equations 10 and 11 it should be appreciated that thetwo alternatives to which block 134 may direct the value of {circumflexover (φ)}_(2,T)(n), namely,

${{{\hat{\phi}}_{2,T}(n)} = {{\frac{\pi}{2}\mspace{14mu}{or}\mspace{14mu}{{\hat{\phi}}_{2,T}(n)}} = \frac{- \pi}{2}}},$provide either a multiplicand of j or −j, respectively, for the terme^(j{circumflex over (φ)}) ^((m)) in Equation 22. Further, to maximizethe term real{y^(H)(n)b₂(n)} from Equation 22 by multiplying times oneof these multiplicands in terms of the term e^(j{circumflex over (φ)})^((m)) , then for a complex number with a positive imaginary portion(extracted by block 120), then the complex number must be multipliedtimes −j. Thus, in the context of FIG. 8, if the complex dot productfrom block 120, after summing with the threshold κ_(odd) by adder 134,has a positive imaginary portion, then the productreal{y^(H)(n)b₂(n)e^(j{circumflex over (φ)}) ^((m)) } is maximized whenφ₂(n)=−π/2, and indeed decision block 134 passes flow to block 140 inthis case to thereby assign the value of −π/2 radians to {circumflexover (φ)}_(2,T)(n). Conversely, for a complex number with a negative orzero imaginary portion, then to maximize the number by multiplying timesone of the multiplicands in terms of the term e^(j{circumflex over (φ)})^(m) the complex number must be multiplied times j. Thus, in the contextof FIG. 8, if the complex dot product from block 120, after summing withthe threshold κ_(odd) by adder 134, has a negative or zero imaginaryvalue, then the product real{y^(H)(n)b₂(n)e^(j{circumflex over (φ)})^((m)) } is maximized when φ₂(n)=π/2, and indeed decision block 134passes flow to block 138 in this case to thereby assign the value of π/2radians to {circumflex over (φ)}_(2,T)(n). Thus, the precedingdemonstrates that Equation 22 is generally maximized by block 100 ₁ whenn is odd, but again with the added ability to offset this determinationin view of the relative value of the feedback error rate, ε.

Concluding the discussion of block 100 ₁, each value of {circumflex over(φ)}_(2,T)(n) determined by block 128 or 130 for an even slot n or byblock 138 or block 140 for an odd slot n is connected to an input oftwo-slot averaging block 132. Block 132 operates to produce, as itsoutput value {circumflex over (ω)}_(2,T)(n), the average of the two mostrecently-received values of {circumflex over (φ)}_(2,T)(n) and{circumflex over (φ)}_(2,T)(n−1). Accordingly, this averaging techniqueapproximates the operation of base station 12 in that it averages inresponse to two successive beamformer coefficients as described earlierwith respect to Equation 17. Further, with respect to block 100 ₁, itsoperation has now shown why the preferred embodiment was introducedearlier to use a type of beamformer verification identified as tworotating hypothesis testing. Specifically from FIG. 8, it may be seenthat for each slot n, one of two hypotheses are tested, that is, for aneven slot n, the two hypotheses correspond to {circumflex over(φ)}_(2,T)(n)∈{0,π}, and for an odd slot n, the two hypothesescorrespond to

${{\hat{\phi}}_{2,T}(n)} \in {\{ {\frac{\pi}{2},\frac{- \pi}{2}} \}.}$Further, the testing is said to rotate in that it alternates betweeneach set of two hypotheses according to whether n is odd or even.

FIG. 9 illustrates a block diagram of a second implementation of abeamformer verification block 100 ₂ that also may be implemented asbeamformer verification block 100 from FIG. 7. Block 100 ₂ operatesaccording to a four hypothesis single shot testing as apparent later andproduces an estimated value designated {circumflex over (ω)}_(2,T)(n),which relates the value {circumflex over (θ)}^((m)) in the followingEquation 30.

$\begin{matrix}{\max\limits_{m \in M}( {{{real}\{ {{y^{H}(n)}{b_{2}(n)}{\mathbb{e}}^{j\;{\hat{\phi}}^{(m)}}} \}} + {\mu(m)}} )} & {{Equation}\mspace{14mu} 30}\end{matrix}$where m is the indexing, M∈{1, 2, 3, 4} is the index set of theallowable {circumflex over (θ)}^((m)) values, μ(m) is a thresholdparameter depending upon m, and where

${{\hat{\theta}}^{(1)} = \frac{\pi}{4}},{{\hat{\theta}}^{(2)} = \frac{3\pi}{4}},{{\hat{\theta}}^{(3)} = \frac{{- 3}\pi}{4}},\;{{{and}\mspace{20mu}{\hat{\theta}}^{(4)}}\mspace{11mu} = {\frac{- \pi}{4}.}}$Block 100 ₂ shares some components with block 100 ₁ of FIG. 8 anddescribed earlier, and for such components like reference numbers arecarried forward from FIG. 8 into FIG. 9; thus, briefly addressing thoseitems, they include the same input values y(n), {circumflex over(α)}_(2,n), and φ₂(n), and the vector formation block 112 thatdetermines the vector elements of b₂(n) as well as the complex dotproduct block 114 which produces the result shown above in Equation 23.The remaining aspects of block 100 ₂ differ in various manners fromblock 100 ₁, as further detailed below.

The dot product from block 114 is connected via its output as a firstmultiplicand to four different multipliers 150, 152, 154, and 156.Further, each of multipliers 150, 152, 154, and 156 receives arespective second multiplicand

${\mathbb{e}}^{j\frac{\pi}{4}},{\mathbb{e}}^{j\frac{3\pi}{4}},{\mathbb{e}}^{j\frac{{- 3}\pi}{4}},{{and}\mspace{11mu}{{\mathbb{e}}^{j\frac{- \pi}{4}}.}}$By way of explanation of these second multiplicands and introduction tothe overall operation of block 100 ₂, block 100 ₂ more directlyaddresses the two-slot averaging performed by base station 12 describedearlier with respect to Equation 17 as compared to block 100 ₁ of FIG.8. Further, it was demonstrates above that given an average between evenand odd slots, the constellation for {circumflex over (θ)}^((m)) is thefour values in the set

$\{ {\frac{\pi}{4},\frac{3\pi}{4},\frac{{- 3}\pi}{4},\frac{- \pi}{4}} \}$as appreciated below this entire constellation is considered by block100 ₂ in one parallel operation. The output of each of multipliers 150,152, 154, and 156 is connected as an input to a respective one of realcomponent extraction blocks 158, 160, 162, and 164, which extract thereal portion of their input values and provide respective outputs as afirst addend to a respective adder 166, 168, 170 and 172. Each adder166, 168, 170 and 172 also receives a second addend from a thresholdblock 174.

Further with respect to threshold block 174, the value of φ₂(n) fromblock 52 is input to an exponential calculation block 176 whichdetermines and outputs the value e^(jφ) ² ^((n)). This output isconnected to a two-slot averaging block 178 which therefore provides theoutput value

$\frac{{\mathbb{e}}^{{j\theta}{(n)}}}{\sqrt{2}}$in response to two successive values, namely, e^(jφ) ² ^((n)) and e^(jφ)² ^((n−1)), and this output is the input to threshold block 174.Further, threshold block 174, like threshold block 124 from FIG. 8, isalso responsive to the feedback bit error rate, ε. For block 100 ₂ ofFIG. 9, however, since its determination relative to Equation 30 is moreprecise by considering the four value constellation for {circumflex over(θ)}^((m)), then further in this regard, the determination of thethreshold from block 174 is more complex. Specifically, threshold block174 determines the actual value of μ(m) from Equation 30, in response toε, and based on the corresponding value of θ(n), as shown in thefollowing Table 4:

TABLE 4${{\mu(m)} = {\frac{{\hat{\sigma}}^{2}}{\sqrt{2}}\ln\;{\rho_{m}( {\theta(n)} )}}},{m = 1},2,3,4$${\theta(n)} = \frac{\pi}{4}$ ${\theta(n)} = \frac{3\pi}{4}$${\theta(n)} = \frac{{- 3}\pi}{4}$ ${\theta(n)} = \frac{- \pi}{4}$ρ₁(θ(n)) (1 − ε)² ε(1 − ε) ε² ε(1 − ε) ρ₂(θ(n)) ε(1 − ε) (1 − ε)² ε(1 −ε) ε² ρ₃(θ(n)) ε² ε(1 − ε) (1 − ε)² ε(1 − ε) ρ₄(θ(n)) ε(1 − ε) ε² ε(1 −ε) (1 − ε)²Further from Table 4, the appropriate value is determined based on m andis provided to the one of adders 166, 168, 170 and 172 corresponding tothe same value for θ(n). For example, for a given value of m and for

${{\theta(n)} = \frac{\pi}{4}},$the determined threshold, μ(m) is provided to adder 166. In any event,each value μ(m) is summed with the corresponding outputs from realcomponent extraction blocks 158, 160, 162, and 164.

The output of each of adders 166, 168, 170 and 172 is connected as aninput to a maximum detection and correlation circuit 180. As furtherdetailed below, circuit 180 determines the largest of its four inputs,and then selects the value of θ(n) that correlates to that value. Forexample, if the maximum input is from adder 166, then circuit 180detects that value and correlates the value of

${\theta(n)} = \frac{\pi}{4}$to that maximum value. Similarly, therefore, one skilled in the art willappreciate the comparable correlation by circuit 180 of

${\theta(n)} = \frac{3\pi}{4}$to a maximum value from adder 168, or of

${\theta(n)} = \frac{{- 3}\pi}{4}$to a maximum value from adder 170, or of

${\theta(n)} = \frac{- \pi}{4}$to a maximum value from adder 172. In any event, the correlated value ofθ(n) is then output by block 100 ₂ as the value {circumflex over(ω)}_(2,T)(n).

An additional detailed explanation of the operation of block 100 ₂should not be necessary to facilitate the understanding of suchoperation by one skilled in the art given the many preceding discussionsof comparable blocks, the operational description above of the variousblocks within block 100 ₂, and the terms in Equation 30. Briefly,therefore, the output of dot product block 114 is multiplied times eachpossible value of θ(n) by multipliers 150, 152, 154, and 156, and thereal portion of the result of each multiplication is extracted therebyproviding the term real{y^(H)(n)b₂e^(j{circumflex over (θ)}) ^((m)) }from Equation 30. In addition, the operation of threshold adjustments byblock 174 and the respective adders is comparable to that describedearlier with respect to block 100 ₁, and is further shown in thatEquation 30 includes the added term of μ(m). Lastly, block 180 selectsthe maximum solution, as is the goal of Equation 30.

Concluding the discussion of block 100 ₂, an embodiment is provided tosolve Equation 30, but it is noted that it is relatively more complexthan that of block 100 ₁ in FIG. 8. For example, block 100 ₂ requiresfour complex multiplications that are not required by block 100 ₁. Onthe other hand, block 100 ₂ directly contemplates the effects of thetwo-slot averaging performed by base station 12 described earlier withrespect to Equation 17. Thus, one skilled in the art may select betweenblocks 100 ₁ and 100 ₂ in view of these considerations as well as otherdesign factors or criteria. Finally, with respect to block 100 ₂ itsoperation has now shown why it was described before to operate as a fourhypothesis single shot testing method in that, for each slot n, fourhypotheses are tested in a single parallel operation, where the fourhypotheses correspond to the cases of

${\theta(n)} = {\{ {\frac{\pi}{4},\frac{3\pi}{4},\frac{{- 3}\pi}{4},\frac{- \pi}{4}} \}.}$

From the above, it may be appreciated that the above embodiments providea single broad range closed loop mode as a replacement to the prior artmodes 1 and 2. The preferred broad range closed loop mode providesnumerous advantageous. For example, the constellation rotation per slotenables ω_(2,T)(n) to encompass an effective constellation of fourpossible values (i.e., 2 values/slot*2 slots/rotation cycle=4 values),and this in conjunction with the smoothing average filter result in anacceptable resolution along with the reduction of effective feedbackdelay for low to moderate channel fading rate. As another example, thebroad range closed loop mode of the preferred embodiments has beensimulated to provide results that match or exceed those of the prior artmodes 1 and 2, but the preferred embodiment use of a single mode inplace of the two prior art modes eliminates the need, and correspondingcomplexity and delay, associated with the prior art requirement ofswitching back and forth between modes 1 and 2. As still anotherbenefit, the preceding teachings may be applied to a base station with anumber of antennas x greater than two antennas; in this case, again afirst value ω₁(n) may be normalized while user station 14 determines thevalues of φ (n) for each of the other x antennas, and a correspondingweight is assigned to each of those values and fed back to the basestation. Again, the determination of φ (n) would be made to maximizeinstantaneous power which may be derived as an extension of Equation 6.As yet another example, the preferred broad range closed loop mode maybe combined with the prior art mode 3 to accommodate the full Dopplerfading range in Table 1. As yet another example of the illustratedbenefits, alternative methods for beamformer verification have beenprovided. As a final example, the present teachings may apply to systemsother than CDMA, which by way of example could include time divisionmultiple access (“TDMA”) and orthogonal frequency division multiplexing(“OFDM”). Indeed, while the present embodiments have been described indetail, various additional substitutions, modifications or alterationscould be made to the descriptions set forth above without departing fromthe inventive scope which is defined by the following claims.

1. A method of transmitting information, comprising the steps of:receiving an information signal; receiving at least one coefficient froma remote communication system; averaging at least one coefficient over aplurality of slots, wherein the at least one coefficient is phaserotated by 90 degrees in each successive slot; producing a plurality ofweighted information signals from the at least one coefficient and theinformation signal; and transmitting the plurality of weightedinformation signals from respective antennas.
 2. A method as in claim 1,comprising the steps of: encoding the information signal; interleavingthe information signal; symbol mapping the information signal; andmodulating the information signal.
 3. A method as in claim 1, whereinthe step of producing a plurality of weighted information signalscomprises the steps of: multiplying the information signal by a firstcoefficient, thereby producing a first weighted information signal; andmultiplying the information signal by a second coefficient, therebyproducing a second weighted information signal.
 4. A method as in claim3, comprising the steps of: transmitting the first weighted informationsignal from a first antenna; and transmitting the second weightedinformation signal from a second antenna.
 5. A method as in claim 1,wherein the respective coefficients correspond respectively topreviously transmitted weighted information signals.
 6. A method as inclaim 1, comprising the steps of: transmitting a first set of pilotsymbols over a common pilot channel; and transmitting a second set ofpilot symbols and the weighted information signals over a dedicatedphysical channel (DPCH).
 7. A method as in claim 1, wherein theaveraging step produces an average coefficient${\omega_{2,T}(n)} = {\frac{1}{2}( {{\mathbb{e}}^{j\;{\phi_{2}{(n)}}} + {\mathbb{e}}^{j\;{\phi_{2}{({n - 1})}}}} )}$over time slots n and n−1.
 8. A method as in claim 7, whereinφ₂(n)∈{0,π}, and wherein φ₂(n−1)∈{π/2,−π/2}.
 9. A method as in claim 7,comprising the step of producing a normalized coefficient.${\omega_{1,T}(n)} = {\frac{1}{\sqrt{2}}.}$
 10. A method as in claim 9,wherein the step of producing a plurality of weighted informationsignals comprises multiplying the information signal by ω_(1,T)(n) andby ω_(2,T)(n).
 11. A method of producing a coefficient in an electronicapparatus, comprising the steps of: receiving in said electronicapparatus a first coefficient corresponding to an even time slot;determining a phase angle is 0 when the first coefficient is 0;determining the phase angle is π when the first coefficient is 1;receiving in said electronic apparatus a second coefficientcorresponding to an odd time slot; determining the phase angle is π/2when the second coefficient is 0; and determining the phase angle is−π/2 when the second coefficient is
 1. 12. A method as in claim 11,wherein the first and second coefficients are received from a remotewireless transmitter.
 13. A method as in claim 11, comprising the stepof averaging the first and second coefficients, wherein the secondcoefficient is phase rotated by 90 degrees with respect to the firstcoefficient.
 14. A method as in claim 13, comprising the step ofproducing a third coefficient${\omega_{2,T}(n)} = {\frac{1}{2}( {{\mathbb{e}}^{j\;{\phi_{2}{(n)}}} + {\mathbb{e}}^{j\;{\phi_{2}{({n - 1})}}}} )}$in response to the step of averaging, wherein n and n−1 are indices ofsequential time slots.
 15. A method as in claim 14, comprising the stepof producing a fourth coefficient.${\omega_{1,T}(n)} = {\frac{1}{\sqrt{2}}.}$
 16. A method as in claim 15,comprising the steps of: multiplying an information signal by the thirdcoefficient, thereby producing a first weighted information signal; andmultiplying the information signal by the fourth coefficient, therebyproducing a second weighted information signal.
 17. A method ofproducing a coefficient, comprising the steps of: receiving a firstcoefficient corresponding to an even time slot; determining a phaseangle is 0 whe the first coefficient is 0; determining the phase angleis π when the first coefficient is 1; receiving a second coefficientcorresponding to an odd time slot; determining the phase angle is π/2when the second coefficient is 0; determining the phase angle is −π/2when the second coefficient is 1; averaging the first and secondcoefficients, wherein the second coefficient is phase rotated by 90degrees with respect to the first coefficient; producing a thirdcoefficient${\omega_{2,T}(n)} = {\frac{1}{2}( {{\mathbb{e}}^{j\;{\phi_{2}{(n)}}} + {\mathbb{e}}^{j\;{\phi_{2}{({n - 1})}}}} )}$in response to the step of averaging, wherein n and n−1 are indices ofsequential time slots; producing a fourth coefficient;${{\omega_{1,T}(n)} = \frac{1}{\sqrt{2}}};$ multiplying an informationsignal by the third coeficient, thereby producing a first weightedinformation signal; multiplying the intormation signal by the fourthcoefficient, thereby producing a second weigthed information signal; andtransmiting the first weighted information signal from a first antenna;and transmitting the second weighted information signal front a secondantenna.
 18. A method of calculating a coefficient, comprising:receiving at least one coefficient from a remote communication system;averaging at least one coefficient over a plurality of slots, whereinthe at least one coefficient is phase rotated by 90 degrees in eachsuccessive slot; and producing a plurality of weighted informationsignals from the at least one coefficient and an information signal. 19.A method as in claim 18, wherein the step of producing a plurality ofweighted information signals comprises the steps of: multiplying theinformation signal by a first coefficient, thereby producing a firstweighted information signal; and multiplying the information signal by asecond coefficient, thereby producing a second weighted informationsignal.
 20. A method as in claim 18, wherein the respective coefficientscorrespond respectively to previously transmitted weighted informationsignals.
 21. A method as in claim 18, wherein the averaging stepproduces an average coefficient${\omega_{2,T}(n)} = {\frac{1}{2}( {{\mathbb{e}}^{j\;{\phi_{2}{(n)}}} + {\mathbb{e}}^{j\;{\phi_{2}{({n - 1})}}}} )}$over time slots n and n−1.
 22. A method as in claim 21, whereinφ₂(n)∈{0,π}, and wherein φ₂(n−1)∈{π/2,−π/2}.
 23. A method as in claim21, comprising the step of producing a normalized coefficient${\omega_{1,T}(n)} = {\frac{1}{\sqrt{2}}.}$
 24. A method as in claim 23,wherein the step of producing a plurality of weighted informationsignals comprises multiplying the information signal by ω_(1,T) (n) andby ω_(2,T) (n).
 25. A transmit circuit, comprising: a feedback circuitcoupled to receive at least one coefficient from a remote communicationsystem, the feedback circuit producing an average of the at least onecoefficient over a plurality of slots, wherein the at least onecoefficient is phase rotated by 90 degrees in each successive slot; afirst multiplier circuit having a first input terminal coupled toreceive an information signal and having a second input terminal coupledto receive the average of the at least one coefficient, the firstmultiplier circuit having an output terminal coupled to receive a firstweighted information signal; and a first transmit antenna coupled to thefirst multiplier circuit output terminal.
 26. A transmit circuit as inclaim 25, comprising: a channel encoder circuit having an input terminalcoupled to receive said information signal and having an outputterminal; an interleaver circuit having an output terminal and having aninput terminal coupled to the output terminal of the channel encodercircuit; a symbol mapper circuit having an output terminal and having aninput terminal coupled to the output terminal of interleaver circuit;and a modulator circuit having an output terminal coupled to the firstinput terminal of the first multiplier circuit and having an inputterminal coupled to the output terminal of symbol mapper circuit.
 27. Atransmit circuit as in claim 25, comprising: a second multiplier circuithaving a first input terminal coupled to receive the information signaland having a second input terminal coupled to receive a normalizedcoefficient, the multiplier circuit having an output terminal coupled toreceive a second weighted information signal; and a second transmitantenna coupled to the second multiplier circuit output terminal.
 28. Atransmit circuit as in claim 27, wherein the normalized coefficient is${\omega_{1,T}(n)} = {\frac{1}{\sqrt{2}}.}$
 29. A transmit circuit as inclaim 25, wherein the at least one coefficient corresponds to apreviously transmitted weighted information signal.
 30. A transmitcircuit as in claim 25, wherein the average of the at least onecoefficient is${\omega_{2,T}(n)} = {\frac{1}{2}( {{\mathbb{e}}^{j\;{\phi_{2}{(n)}}} + {\mathbb{e}}^{j\;{\phi_{2}{({n - 1})}}}} )}$over time slots n and n−1.
 31. A transmit circuit as in claim 30,wherein φ₂(n)∈{0,π}, and wherein φ₂(n−1)∈{π/2,−π/2}.